930 KiB
930 KiB
import numpy as np
# Требуемые модули из sklearn
from sklearn.datasets import make_classification
from sklearn.metrics import confusion_matrix, classification_report, accuracy_score, roc_auc_score
from sklearn.model_selection import train_test_split
from sklearn.neighbors import KNeighborsClassifier
#Графики
import matplotlib.pyplot as pltdef plot_2d_separator(classifier, X, fill=False, line=True, ax=None, eps=None):
if eps is None:
eps = 1.0 #X.std() / 2.
x_min, x_max = X[:, 0].min() - eps, X[:, 0].max() + eps
y_min, y_max = X[:, 1].min() - eps, X[:, 1].max() + eps
xx = np.linspace(x_min, x_max, 100)
yy = np.linspace(y_min, y_max, 100)
X1, X2 = np.meshgrid(xx, yy)
X_grid = np.c_[X1.ravel(), X2.ravel()]
try:
decision_values = classifier.decision_function(X_grid)
levels = [0]
fill_levels = [decision_values.min(), 0, decision_values.max()]
except AttributeError:
# no decision_function
decision_values = classifier.predict_proba(X_grid)[:, 1]
levels = [.5]
fill_levels = [0, .5, 1]
if ax is None:
ax = plt.gca()
if fill:
ax.contourf(X1, X2, decision_values.reshape(X1.shape),
levels=fill_levels, colors=['cyan', 'pink', 'yellow'])
if line:
ax.contour(X1, X2, decision_values.reshape(X1.shape), levels=levels, colors="black")
ax.set_xlim(x_min, x_max)
ax.set_ylim(y_min, y_max)
ax.set_xticks(())
ax.set_yticks(())X, y = make_classification(n_features=2, random_state = 78, class_sep = 0.45, n_redundant=0, n_informative=1, n_clusters_per_class=1, n_samples = 1000)print ("Координаты точек: ")
print (X[:15])
print ("Метки класса: ")
print (y[:15])Координаты точек:
[[ 1.48828264e+00 -7.10442604e-01]
[-7.10253928e-01 6.93938341e-01]
[ 5.33444250e-01 -1.31136377e+00]
[ 1.08104452e+00 5.34466225e-01]
[-3.97224728e-01 1.29783335e-01]
[ 1.12862644e-01 5.10913913e-01]
[ 7.13520454e-04 7.42926105e-01]
[-1.50699375e+00 -1.51932200e+00]
[-7.09257115e-01 4.58339246e-01]
[-1.51395805e+00 -1.13202013e-01]
[ 1.64173194e+00 5.62099713e-01]
[-2.07311044e+00 -7.20098263e-01]
[ 1.21634891e+00 4.34451064e-01]
[-1.39209028e+00 5.71283980e-01]
[ 4.57465767e-01 5.26568280e-01]]
Метки класса:
[0 1 0 1 0 1 0 0 1 0 1 0 1 1 1]
plt.scatter (X[:,0], X[:,1], c=y)
plt.show<function matplotlib.pyplot.show(close=None, block=None)>
X_train, X_test, y_train, y_test = train_test_split(X, y, test_size = 0.25, random_state = 3)plt.figure(figsize=(7, 5))
# Обучающая выборка
plt.scatter(
X_train[:, 0], X_train[:, 1],
c=y_train,
label="train"
)
plt.title("Обучающая выборка")
plt.xlabel("x1")
plt.ylabel("x2")
plt.grid(True, alpha=0.3)
plt.show()
plt.figure(figsize=(7, 5))
# Тестовая выборка
plt.scatter(
X_test[:, 0], X_test[:, 1],
c=y_test,
label="test"
)
plt.title("Тестовая выборка")
plt.xlabel("x1")
plt.ylabel("x2")
plt.grid(True, alpha=0.3)
plt.show()
#RS_1knn = KNeighborsClassifier(n_neighbors=1, metric = 'euclidean')knn.fit(X_train, y_train)
<style>#sk-container-id-1 {
/* Definition of color scheme common for light and dark mode */
--sklearn-color-text: #000;
--sklearn-color-text-muted: #666;
--sklearn-color-line: gray;
/* Definition of color scheme for unfitted estimators */
--sklearn-color-unfitted-level-0: #fff5e6;
--sklearn-color-unfitted-level-1: #f6e4d2;
--sklearn-color-unfitted-level-2: #ffe0b3;
--sklearn-color-unfitted-level-3: chocolate;
/* Definition of color scheme for fitted estimators */
--sklearn-color-fitted-level-0: #f0f8ff;
--sklearn-color-fitted-level-1: #d4ebff;
--sklearn-color-fitted-level-2: #b3dbfd;
--sklearn-color-fitted-level-3: cornflowerblue;
/* Specific color for light theme */
--sklearn-color-text-on-default-background: var(--sg-text-color, var(--theme-code-foreground, var(--jp-content-font-color1, black)));
--sklearn-color-background: var(--sg-background-color, var(--theme-background, var(--jp-layout-color0, white)));
--sklearn-color-border-box: var(--sg-text-color, var(--theme-code-foreground, var(--jp-content-font-color1, black)));
--sklearn-color-icon: #696969;
@media (prefers-color-scheme: dark) {
/* Redefinition of color scheme for dark theme */
--sklearn-color-text-on-default-background: var(--sg-text-color, var(--theme-code-foreground, var(--jp-content-font-color1, white)));
--sklearn-color-background: var(--sg-background-color, var(--theme-background, var(--jp-layout-color0, #111)));
--sklearn-color-border-box: var(--sg-text-color, var(--theme-code-foreground, var(--jp-content-font-color1, white)));
--sklearn-color-icon: #878787;
}
}
#sk-container-id-1 {
color: var(--sklearn-color-text);
}
#sk-container-id-1 pre {
padding: 0;
}
#sk-container-id-1 input.sk-hidden--visually {
border: 0;
clip: rect(1px 1px 1px 1px);
clip: rect(1px, 1px, 1px, 1px);
height: 1px;
margin: -1px;
overflow: hidden;
padding: 0;
position: absolute;
width: 1px;
}
#sk-container-id-1 div.sk-dashed-wrapped {
border: 1px dashed var(--sklearn-color-line);
margin: 0 0.4em 0.5em 0.4em;
box-sizing: border-box;
padding-bottom: 0.4em;
background-color: var(--sklearn-color-background);
}
#sk-container-id-1 div.sk-container {
/* jupyter's `normalize.less` sets `[hidden] { display: none; }`
but bootstrap.min.css set `[hidden] { display: none !important; }`
so we also need the `!important` here to be able to override the
default hidden behavior on the sphinx rendered scikit-learn.org.
See: https://github.com/scikit-learn/scikit-learn/issues/21755 */
display: inline-block !important;
position: relative;
}
#sk-container-id-1 div.sk-text-repr-fallback {
display: none;
}
div.sk-parallel-item,
div.sk-serial,
div.sk-item {
/* draw centered vertical line to link estimators */
background-image: linear-gradient(var(--sklearn-color-text-on-default-background), var(--sklearn-color-text-on-default-background));
background-size: 2px 100%;
background-repeat: no-repeat;
background-position: center center;
}
/* Parallel-specific style estimator block */
#sk-container-id-1 div.sk-parallel-item::after {
content: "";
width: 100%;
border-bottom: 2px solid var(--sklearn-color-text-on-default-background);
flex-grow: 1;
}
#sk-container-id-1 div.sk-parallel {
display: flex;
align-items: stretch;
justify-content: center;
background-color: var(--sklearn-color-background);
position: relative;
}
#sk-container-id-1 div.sk-parallel-item {
display: flex;
flex-direction: column;
}
#sk-container-id-1 div.sk-parallel-item:first-child::after {
align-self: flex-end;
width: 50%;
}
#sk-container-id-1 div.sk-parallel-item:last-child::after {
align-self: flex-start;
width: 50%;
}
#sk-container-id-1 div.sk-parallel-item:only-child::after {
width: 0;
}
/* Serial-specific style estimator block */
#sk-container-id-1 div.sk-serial {
display: flex;
flex-direction: column;
align-items: center;
background-color: var(--sklearn-color-background);
padding-right: 1em;
padding-left: 1em;
}
/* Toggleable style: style used for estimator/Pipeline/ColumnTransformer box that is
clickable and can be expanded/collapsed.
- Pipeline and ColumnTransformer use this feature and define the default style
- Estimators will overwrite some part of the style using the `sk-estimator` class
*/
/* Pipeline and ColumnTransformer style (default) */
#sk-container-id-1 div.sk-toggleable {
/* Default theme specific background. It is overwritten whether we have a
specific estimator or a Pipeline/ColumnTransformer */
background-color: var(--sklearn-color-background);
}
/* Toggleable label */
#sk-container-id-1 label.sk-toggleable__label {
cursor: pointer;
display: flex;
width: 100%;
margin-bottom: 0;
padding: 0.5em;
box-sizing: border-box;
text-align: center;
align-items: start;
justify-content: space-between;
gap: 0.5em;
}
#sk-container-id-1 label.sk-toggleable__label .caption {
font-size: 0.6rem;
font-weight: lighter;
color: var(--sklearn-color-text-muted);
}
#sk-container-id-1 label.sk-toggleable__label-arrow:before {
/* Arrow on the left of the label */
content: "▸";
float: left;
margin-right: 0.25em;
color: var(--sklearn-color-icon);
}
#sk-container-id-1 label.sk-toggleable__label-arrow:hover:before {
color: var(--sklearn-color-text);
}
/* Toggleable content - dropdown */
#sk-container-id-1 div.sk-toggleable__content {
display: none;
text-align: left;
/* unfitted */
background-color: var(--sklearn-color-unfitted-level-0);
}
#sk-container-id-1 div.sk-toggleable__content.fitted {
/* fitted */
background-color: var(--sklearn-color-fitted-level-0);
}
#sk-container-id-1 div.sk-toggleable__content pre {
margin: 0.2em;
border-radius: 0.25em;
color: var(--sklearn-color-text);
/* unfitted */
background-color: var(--sklearn-color-unfitted-level-0);
}
#sk-container-id-1 div.sk-toggleable__content.fitted pre {
/* unfitted */
background-color: var(--sklearn-color-fitted-level-0);
}
#sk-container-id-1 input.sk-toggleable__control:checked~div.sk-toggleable__content {
/* Expand drop-down */
display: block;
width: 100%;
overflow: visible;
}
#sk-container-id-1 input.sk-toggleable__control:checked~label.sk-toggleable__label-arrow:before {
content: "▾";
}
/* Pipeline/ColumnTransformer-specific style */
#sk-container-id-1 div.sk-label input.sk-toggleable__control:checked~label.sk-toggleable__label {
color: var(--sklearn-color-text);
background-color: var(--sklearn-color-unfitted-level-2);
}
#sk-container-id-1 div.sk-label.fitted input.sk-toggleable__control:checked~label.sk-toggleable__label {
background-color: var(--sklearn-color-fitted-level-2);
}
/* Estimator-specific style */
/* Colorize estimator box */
#sk-container-id-1 div.sk-estimator input.sk-toggleable__control:checked~label.sk-toggleable__label {
/* unfitted */
background-color: var(--sklearn-color-unfitted-level-2);
}
#sk-container-id-1 div.sk-estimator.fitted input.sk-toggleable__control:checked~label.sk-toggleable__label {
/* fitted */
background-color: var(--sklearn-color-fitted-level-2);
}
#sk-container-id-1 div.sk-label label.sk-toggleable__label,
#sk-container-id-1 div.sk-label label {
/* The background is the default theme color */
color: var(--sklearn-color-text-on-default-background);
}
/* On hover, darken the color of the background */
#sk-container-id-1 div.sk-label:hover label.sk-toggleable__label {
color: var(--sklearn-color-text);
background-color: var(--sklearn-color-unfitted-level-2);
}
/* Label box, darken color on hover, fitted */
#sk-container-id-1 div.sk-label.fitted:hover label.sk-toggleable__label.fitted {
color: var(--sklearn-color-text);
background-color: var(--sklearn-color-fitted-level-2);
}
/* Estimator label */
#sk-container-id-1 div.sk-label label {
font-family: monospace;
font-weight: bold;
display: inline-block;
line-height: 1.2em;
}
#sk-container-id-1 div.sk-label-container {
text-align: center;
}
/* Estimator-specific */
#sk-container-id-1 div.sk-estimator {
font-family: monospace;
border: 1px dotted var(--sklearn-color-border-box);
border-radius: 0.25em;
box-sizing: border-box;
margin-bottom: 0.5em;
/* unfitted */
background-color: var(--sklearn-color-unfitted-level-0);
}
#sk-container-id-1 div.sk-estimator.fitted {
/* fitted */
background-color: var(--sklearn-color-fitted-level-0);
}
/* on hover */
#sk-container-id-1 div.sk-estimator:hover {
/* unfitted */
background-color: var(--sklearn-color-unfitted-level-2);
}
#sk-container-id-1 div.sk-estimator.fitted:hover {
/* fitted */
background-color: var(--sklearn-color-fitted-level-2);
}
/* Specification for estimator info (e.g. "i" and "?") */
/* Common style for "i" and "?" */
.sk-estimator-doc-link,
a:link.sk-estimator-doc-link,
a:visited.sk-estimator-doc-link {
float: right;
font-size: smaller;
line-height: 1em;
font-family: monospace;
background-color: var(--sklearn-color-background);
border-radius: 1em;
height: 1em;
width: 1em;
text-decoration: none !important;
margin-left: 0.5em;
text-align: center;
/* unfitted */
border: var(--sklearn-color-unfitted-level-1) 1pt solid;
color: var(--sklearn-color-unfitted-level-1);
}
.sk-estimator-doc-link.fitted,
a:link.sk-estimator-doc-link.fitted,
a:visited.sk-estimator-doc-link.fitted {
/* fitted */
border: var(--sklearn-color-fitted-level-1) 1pt solid;
color: var(--sklearn-color-fitted-level-1);
}
/* On hover */
div.sk-estimator:hover .sk-estimator-doc-link:hover,
.sk-estimator-doc-link:hover,
div.sk-label-container:hover .sk-estimator-doc-link:hover,
.sk-estimator-doc-link:hover {
/* unfitted */
background-color: var(--sklearn-color-unfitted-level-3);
color: var(--sklearn-color-background);
text-decoration: none;
}
div.sk-estimator.fitted:hover .sk-estimator-doc-link.fitted:hover,
.sk-estimator-doc-link.fitted:hover,
div.sk-label-container:hover .sk-estimator-doc-link.fitted:hover,
.sk-estimator-doc-link.fitted:hover {
/* fitted */
background-color: var(--sklearn-color-fitted-level-3);
color: var(--sklearn-color-background);
text-decoration: none;
}
/* Span, style for the box shown on hovering the info icon */
.sk-estimator-doc-link span {
display: none;
z-index: 9999;
position: relative;
font-weight: normal;
right: .2ex;
padding: .5ex;
margin: .5ex;
width: min-content;
min-width: 20ex;
max-width: 50ex;
color: var(--sklearn-color-text);
box-shadow: 2pt 2pt 4pt #999;
/* unfitted */
background: var(--sklearn-color-unfitted-level-0);
border: .5pt solid var(--sklearn-color-unfitted-level-3);
}
.sk-estimator-doc-link.fitted span {
/* fitted */
background: var(--sklearn-color-fitted-level-0);
border: var(--sklearn-color-fitted-level-3);
}
.sk-estimator-doc-link:hover span {
display: block;
}
/* "?"-specific style due to the `` HTML tag */
#sk-container-id-1 a.estimator_doc_link {
float: right;
font-size: 1rem;
line-height: 1em;
font-family: monospace;
background-color: var(--sklearn-color-background);
border-radius: 1rem;
height: 1rem;
width: 1rem;
text-decoration: none;
/* unfitted */
color: var(--sklearn-color-unfitted-level-1);
border: var(--sklearn-color-unfitted-level-1) 1pt solid;
}
#sk-container-id-1 a.estimator_doc_link.fitted {
/* fitted */
border: var(--sklearn-color-fitted-level-1) 1pt solid;
color: var(--sklearn-color-fitted-level-1);
}
/* On hover */
#sk-container-id-1 a.estimator_doc_link:hover {
/* unfitted */
background-color: var(--sklearn-color-unfitted-level-3);
color: var(--sklearn-color-background);
text-decoration: none;
}
#sk-container-id-1 a.estimator_doc_link.fitted:hover {
/* fitted */
background-color: var(--sklearn-color-fitted-level-3);
}
.estimator-table summary {
padding: .5rem;
font-family: monospace;
cursor: pointer;
}
.estimator-table details[open] {
padding-left: 0.1rem;
padding-right: 0.1rem;
padding-bottom: 0.3rem;
}
.estimator-table .parameters-table {
margin-left: auto !important;
margin-right: auto !important;
}
.estimator-table .parameters-table tr:nth-child(odd) {
background-color: #fff;
}
.estimator-table .parameters-table tr:nth-child(even) {
background-color: #f6f6f6;
}
.estimator-table .parameters-table tr:hover {
background-color: #e0e0e0;
}
.estimator-table table td {
border: 1px solid rgba(106, 105, 104, 0.232);
}
.user-set td {
color:rgb(255, 94, 0);
text-align: left;
}
.user-set td.value pre {
color:rgb(255, 94, 0) !important;
background-color: transparent !important;
}
.default td {
color: black;
text-align: left;
}
.user-set td i,
.default td i {
color: black;
}
.copy-paste-icon {
background-image: url(data:image/svg+xml;base64,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);
background-repeat: no-repeat;
background-size: 14px 14px;
background-position: 0;
display: inline-block;
width: 14px;
height: 14px;
cursor: pointer;
}
</style>
On GitHub, the HTML representation is unable to render, please try loading this page with nbviewer.org.
<script>function copyToClipboard(text, element) {
// Get the parameter prefix from the closest toggleable content
const toggleableContent = element.closest('.sk-toggleable__content');
const paramPrefix = toggleableContent ? toggleableContent.dataset.paramPrefix : '';
const fullParamName = paramPrefix ? `${paramPrefix}${text}` : text;
const originalStyle = element.style;
const computedStyle = window.getComputedStyle(element);
const originalWidth = computedStyle.width;
const originalHTML = element.innerHTML.replace('Copied!', '');
navigator.clipboard.writeText(fullParamName)
.then(() => {
element.style.width = originalWidth;
element.style.color = 'green';
element.innerHTML = "Copied!";
setTimeout(() => {
element.innerHTML = originalHTML;
element.style = originalStyle;
}, 2000);
})
.catch(err => {
console.error('Failed to copy:', err);
element.style.color = 'red';
element.innerHTML = "Failed!";
setTimeout(() => {
element.innerHTML = originalHTML;
element.style = originalStyle;
}, 2000);
});
return false;
}
document.querySelectorAll('.fa-regular.fa-copy').forEach(function(element) {
const toggleableContent = element.closest('.sk-toggleable__content');
const paramPrefix = toggleableContent ? toggleableContent.dataset.paramPrefix : '';
const paramName = element.parentElement.nextElementSibling.textContent.trim();
const fullParamName = paramPrefix ? `${paramPrefix}${paramName}` : paramName;
element.setAttribute('title', fullParamName);
});
</script>
KNeighborsClassifier(metric='euclidean', n_neighbors=1)In a Jupyter environment, please rerun this cell to show the HTML representation or trust the notebook.
On GitHub, the HTML representation is unable to render, please try loading this page with nbviewer.org.
Parameters
| n_neighbors | 1 | |
| weights | 'uniform' | |
| algorithm | 'auto' | |
| leaf_size | 30 | |
| p | 2 | |
| metric | 'euclidean' | |
| metric_params | None | |
| n_jobs | None |
prediction = knn.predict(X_test)print ('Prediction and test: ')
print (prediction)
print (y_test)Prediction and test:
[1 1 0 0 0 1 1 1 0 0 1 0 0 0 0 1 1 0 1 1 0 0 1 0 1 0 0 1 0 0 0 1 1 0 0 0 1
1 0 1 1 0 0 1 0 1 1 1 0 1 0 1 1 0 1 1 0 1 0 0 1 1 1 0 0 1 1 1 1 1 0 0 0 0
0 0 1 0 1 1 0 1 1 1 1 0 1 1 0 0 0 1 0 1 1 1 0 1 1 1 0 0 0 1 0 0 0 1 1 1 1
0 0 1 0 0 0 0 0 0 0 1 0 1 1 1 0 1 0 0 0 0 1 1 1 1 1 1 1 1 0 0 0 0 0 1 0 1
0 1 0 0 0 0 0 1 1 0 1 1 0 1 1 0 0 0 1 0 0 1 1 0 1 0 0 0 1 1 1 1 0 1 0 0 1
0 0 1 1 1 0 1 0 0 1 1 1 1 1 1 0 1 1 1 1 1 1 0 1 1 1 1 1 1 0 1 0 0 0 0 0 0
1 0 0 0 0 0 0 0 1 0 1 0 0 1 0 1 1 0 1 1 1 1 1 0 1 0 0 1]
[1 1 0 0 0 0 1 1 0 0 0 0 0 0 0 1 1 0 1 0 0 0 0 0 1 0 0 1 0 0 0 1 1 0 0 0 1
1 0 1 1 0 0 1 1 1 1 1 0 0 0 1 0 0 1 1 0 1 1 0 1 1 0 0 0 1 1 1 0 1 1 1 0 0
0 0 0 0 1 1 0 1 0 1 1 0 1 1 0 0 1 1 0 1 1 1 0 1 1 1 0 0 0 0 0 0 0 1 0 1 1
0 0 0 1 0 0 0 0 0 0 1 0 1 1 0 1 1 0 0 0 0 1 1 1 1 1 1 1 1 1 0 0 0 1 0 0 1
0 0 0 0 0 0 0 0 0 0 1 1 0 1 1 0 0 0 1 0 0 1 1 0 1 1 0 0 1 1 1 1 0 1 0 0 1
0 0 0 1 1 0 1 0 1 1 1 1 0 1 1 1 1 0 1 1 1 1 1 1 1 0 1 0 1 1 1 0 0 0 0 0 0
0 0 1 1 0 0 0 0 1 0 1 0 1 1 0 1 1 0 1 1 1 0 1 0 1 1 0 1]
print ('Confusion matrix: ')
print (confusion_matrix(y_test, prediction))Confusion matrix:
[[105 25]
[ 18 102]]
print ('Accuracy score: ', accuracy_score(prediction, y_test))Accuracy score: 0.828
print(classification_report(y_test, prediction)) precision recall f1-score support
0 0.85 0.81 0.83 130
1 0.80 0.85 0.83 120
accuracy 0.83 250
macro avg 0.83 0.83 0.83 250
weighted avg 0.83 0.83 0.83 250
roc_auc_score(y_test, prediction)0.8288461538461539plt.xlabel("first feature")
plt.ylabel("second feature")
plot_2d_separator(knn, X, fill=True)
plt.scatter(X[:, 0], X[:, 1], c=y, s=70)<matplotlib.collections.PathCollection at 0x9794e90>
#RS_3knn = KNeighborsClassifier(n_neighbors=3, metric = 'euclidean')knn.fit(X_train, y_train)
<style>#sk-container-id-2 {
/* Definition of color scheme common for light and dark mode */
--sklearn-color-text: #000;
--sklearn-color-text-muted: #666;
--sklearn-color-line: gray;
/* Definition of color scheme for unfitted estimators */
--sklearn-color-unfitted-level-0: #fff5e6;
--sklearn-color-unfitted-level-1: #f6e4d2;
--sklearn-color-unfitted-level-2: #ffe0b3;
--sklearn-color-unfitted-level-3: chocolate;
/* Definition of color scheme for fitted estimators */
--sklearn-color-fitted-level-0: #f0f8ff;
--sklearn-color-fitted-level-1: #d4ebff;
--sklearn-color-fitted-level-2: #b3dbfd;
--sklearn-color-fitted-level-3: cornflowerblue;
/* Specific color for light theme */
--sklearn-color-text-on-default-background: var(--sg-text-color, var(--theme-code-foreground, var(--jp-content-font-color1, black)));
--sklearn-color-background: var(--sg-background-color, var(--theme-background, var(--jp-layout-color0, white)));
--sklearn-color-border-box: var(--sg-text-color, var(--theme-code-foreground, var(--jp-content-font-color1, black)));
--sklearn-color-icon: #696969;
@media (prefers-color-scheme: dark) {
/* Redefinition of color scheme for dark theme */
--sklearn-color-text-on-default-background: var(--sg-text-color, var(--theme-code-foreground, var(--jp-content-font-color1, white)));
--sklearn-color-background: var(--sg-background-color, var(--theme-background, var(--jp-layout-color0, #111)));
--sklearn-color-border-box: var(--sg-text-color, var(--theme-code-foreground, var(--jp-content-font-color1, white)));
--sklearn-color-icon: #878787;
}
}
#sk-container-id-2 {
color: var(--sklearn-color-text);
}
#sk-container-id-2 pre {
padding: 0;
}
#sk-container-id-2 input.sk-hidden--visually {
border: 0;
clip: rect(1px 1px 1px 1px);
clip: rect(1px, 1px, 1px, 1px);
height: 1px;
margin: -1px;
overflow: hidden;
padding: 0;
position: absolute;
width: 1px;
}
#sk-container-id-2 div.sk-dashed-wrapped {
border: 1px dashed var(--sklearn-color-line);
margin: 0 0.4em 0.5em 0.4em;
box-sizing: border-box;
padding-bottom: 0.4em;
background-color: var(--sklearn-color-background);
}
#sk-container-id-2 div.sk-container {
/* jupyter's `normalize.less` sets `[hidden] { display: none; }`
but bootstrap.min.css set `[hidden] { display: none !important; }`
so we also need the `!important` here to be able to override the
default hidden behavior on the sphinx rendered scikit-learn.org.
See: https://github.com/scikit-learn/scikit-learn/issues/21755 */
display: inline-block !important;
position: relative;
}
#sk-container-id-2 div.sk-text-repr-fallback {
display: none;
}
div.sk-parallel-item,
div.sk-serial,
div.sk-item {
/* draw centered vertical line to link estimators */
background-image: linear-gradient(var(--sklearn-color-text-on-default-background), var(--sklearn-color-text-on-default-background));
background-size: 2px 100%;
background-repeat: no-repeat;
background-position: center center;
}
/* Parallel-specific style estimator block */
#sk-container-id-2 div.sk-parallel-item::after {
content: "";
width: 100%;
border-bottom: 2px solid var(--sklearn-color-text-on-default-background);
flex-grow: 1;
}
#sk-container-id-2 div.sk-parallel {
display: flex;
align-items: stretch;
justify-content: center;
background-color: var(--sklearn-color-background);
position: relative;
}
#sk-container-id-2 div.sk-parallel-item {
display: flex;
flex-direction: column;
}
#sk-container-id-2 div.sk-parallel-item:first-child::after {
align-self: flex-end;
width: 50%;
}
#sk-container-id-2 div.sk-parallel-item:last-child::after {
align-self: flex-start;
width: 50%;
}
#sk-container-id-2 div.sk-parallel-item:only-child::after {
width: 0;
}
/* Serial-specific style estimator block */
#sk-container-id-2 div.sk-serial {
display: flex;
flex-direction: column;
align-items: center;
background-color: var(--sklearn-color-background);
padding-right: 1em;
padding-left: 1em;
}
/* Toggleable style: style used for estimator/Pipeline/ColumnTransformer box that is
clickable and can be expanded/collapsed.
- Pipeline and ColumnTransformer use this feature and define the default style
- Estimators will overwrite some part of the style using the `sk-estimator` class
*/
/* Pipeline and ColumnTransformer style (default) */
#sk-container-id-2 div.sk-toggleable {
/* Default theme specific background. It is overwritten whether we have a
specific estimator or a Pipeline/ColumnTransformer */
background-color: var(--sklearn-color-background);
}
/* Toggleable label */
#sk-container-id-2 label.sk-toggleable__label {
cursor: pointer;
display: flex;
width: 100%;
margin-bottom: 0;
padding: 0.5em;
box-sizing: border-box;
text-align: center;
align-items: start;
justify-content: space-between;
gap: 0.5em;
}
#sk-container-id-2 label.sk-toggleable__label .caption {
font-size: 0.6rem;
font-weight: lighter;
color: var(--sklearn-color-text-muted);
}
#sk-container-id-2 label.sk-toggleable__label-arrow:before {
/* Arrow on the left of the label */
content: "▸";
float: left;
margin-right: 0.25em;
color: var(--sklearn-color-icon);
}
#sk-container-id-2 label.sk-toggleable__label-arrow:hover:before {
color: var(--sklearn-color-text);
}
/* Toggleable content - dropdown */
#sk-container-id-2 div.sk-toggleable__content {
display: none;
text-align: left;
/* unfitted */
background-color: var(--sklearn-color-unfitted-level-0);
}
#sk-container-id-2 div.sk-toggleable__content.fitted {
/* fitted */
background-color: var(--sklearn-color-fitted-level-0);
}
#sk-container-id-2 div.sk-toggleable__content pre {
margin: 0.2em;
border-radius: 0.25em;
color: var(--sklearn-color-text);
/* unfitted */
background-color: var(--sklearn-color-unfitted-level-0);
}
#sk-container-id-2 div.sk-toggleable__content.fitted pre {
/* unfitted */
background-color: var(--sklearn-color-fitted-level-0);
}
#sk-container-id-2 input.sk-toggleable__control:checked~div.sk-toggleable__content {
/* Expand drop-down */
display: block;
width: 100%;
overflow: visible;
}
#sk-container-id-2 input.sk-toggleable__control:checked~label.sk-toggleable__label-arrow:before {
content: "▾";
}
/* Pipeline/ColumnTransformer-specific style */
#sk-container-id-2 div.sk-label input.sk-toggleable__control:checked~label.sk-toggleable__label {
color: var(--sklearn-color-text);
background-color: var(--sklearn-color-unfitted-level-2);
}
#sk-container-id-2 div.sk-label.fitted input.sk-toggleable__control:checked~label.sk-toggleable__label {
background-color: var(--sklearn-color-fitted-level-2);
}
/* Estimator-specific style */
/* Colorize estimator box */
#sk-container-id-2 div.sk-estimator input.sk-toggleable__control:checked~label.sk-toggleable__label {
/* unfitted */
background-color: var(--sklearn-color-unfitted-level-2);
}
#sk-container-id-2 div.sk-estimator.fitted input.sk-toggleable__control:checked~label.sk-toggleable__label {
/* fitted */
background-color: var(--sklearn-color-fitted-level-2);
}
#sk-container-id-2 div.sk-label label.sk-toggleable__label,
#sk-container-id-2 div.sk-label label {
/* The background is the default theme color */
color: var(--sklearn-color-text-on-default-background);
}
/* On hover, darken the color of the background */
#sk-container-id-2 div.sk-label:hover label.sk-toggleable__label {
color: var(--sklearn-color-text);
background-color: var(--sklearn-color-unfitted-level-2);
}
/* Label box, darken color on hover, fitted */
#sk-container-id-2 div.sk-label.fitted:hover label.sk-toggleable__label.fitted {
color: var(--sklearn-color-text);
background-color: var(--sklearn-color-fitted-level-2);
}
/* Estimator label */
#sk-container-id-2 div.sk-label label {
font-family: monospace;
font-weight: bold;
display: inline-block;
line-height: 1.2em;
}
#sk-container-id-2 div.sk-label-container {
text-align: center;
}
/* Estimator-specific */
#sk-container-id-2 div.sk-estimator {
font-family: monospace;
border: 1px dotted var(--sklearn-color-border-box);
border-radius: 0.25em;
box-sizing: border-box;
margin-bottom: 0.5em;
/* unfitted */
background-color: var(--sklearn-color-unfitted-level-0);
}
#sk-container-id-2 div.sk-estimator.fitted {
/* fitted */
background-color: var(--sklearn-color-fitted-level-0);
}
/* on hover */
#sk-container-id-2 div.sk-estimator:hover {
/* unfitted */
background-color: var(--sklearn-color-unfitted-level-2);
}
#sk-container-id-2 div.sk-estimator.fitted:hover {
/* fitted */
background-color: var(--sklearn-color-fitted-level-2);
}
/* Specification for estimator info (e.g. "i" and "?") */
/* Common style for "i" and "?" */
.sk-estimator-doc-link,
a:link.sk-estimator-doc-link,
a:visited.sk-estimator-doc-link {
float: right;
font-size: smaller;
line-height: 1em;
font-family: monospace;
background-color: var(--sklearn-color-background);
border-radius: 1em;
height: 1em;
width: 1em;
text-decoration: none !important;
margin-left: 0.5em;
text-align: center;
/* unfitted */
border: var(--sklearn-color-unfitted-level-1) 1pt solid;
color: var(--sklearn-color-unfitted-level-1);
}
.sk-estimator-doc-link.fitted,
a:link.sk-estimator-doc-link.fitted,
a:visited.sk-estimator-doc-link.fitted {
/* fitted */
border: var(--sklearn-color-fitted-level-1) 1pt solid;
color: var(--sklearn-color-fitted-level-1);
}
/* On hover */
div.sk-estimator:hover .sk-estimator-doc-link:hover,
.sk-estimator-doc-link:hover,
div.sk-label-container:hover .sk-estimator-doc-link:hover,
.sk-estimator-doc-link:hover {
/* unfitted */
background-color: var(--sklearn-color-unfitted-level-3);
color: var(--sklearn-color-background);
text-decoration: none;
}
div.sk-estimator.fitted:hover .sk-estimator-doc-link.fitted:hover,
.sk-estimator-doc-link.fitted:hover,
div.sk-label-container:hover .sk-estimator-doc-link.fitted:hover,
.sk-estimator-doc-link.fitted:hover {
/* fitted */
background-color: var(--sklearn-color-fitted-level-3);
color: var(--sklearn-color-background);
text-decoration: none;
}
/* Span, style for the box shown on hovering the info icon */
.sk-estimator-doc-link span {
display: none;
z-index: 9999;
position: relative;
font-weight: normal;
right: .2ex;
padding: .5ex;
margin: .5ex;
width: min-content;
min-width: 20ex;
max-width: 50ex;
color: var(--sklearn-color-text);
box-shadow: 2pt 2pt 4pt #999;
/* unfitted */
background: var(--sklearn-color-unfitted-level-0);
border: .5pt solid var(--sklearn-color-unfitted-level-3);
}
.sk-estimator-doc-link.fitted span {
/* fitted */
background: var(--sklearn-color-fitted-level-0);
border: var(--sklearn-color-fitted-level-3);
}
.sk-estimator-doc-link:hover span {
display: block;
}
/* "?"-specific style due to the `` HTML tag */
#sk-container-id-2 a.estimator_doc_link {
float: right;
font-size: 1rem;
line-height: 1em;
font-family: monospace;
background-color: var(--sklearn-color-background);
border-radius: 1rem;
height: 1rem;
width: 1rem;
text-decoration: none;
/* unfitted */
color: var(--sklearn-color-unfitted-level-1);
border: var(--sklearn-color-unfitted-level-1) 1pt solid;
}
#sk-container-id-2 a.estimator_doc_link.fitted {
/* fitted */
border: var(--sklearn-color-fitted-level-1) 1pt solid;
color: var(--sklearn-color-fitted-level-1);
}
/* On hover */
#sk-container-id-2 a.estimator_doc_link:hover {
/* unfitted */
background-color: var(--sklearn-color-unfitted-level-3);
color: var(--sklearn-color-background);
text-decoration: none;
}
#sk-container-id-2 a.estimator_doc_link.fitted:hover {
/* fitted */
background-color: var(--sklearn-color-fitted-level-3);
}
.estimator-table summary {
padding: .5rem;
font-family: monospace;
cursor: pointer;
}
.estimator-table details[open] {
padding-left: 0.1rem;
padding-right: 0.1rem;
padding-bottom: 0.3rem;
}
.estimator-table .parameters-table {
margin-left: auto !important;
margin-right: auto !important;
}
.estimator-table .parameters-table tr:nth-child(odd) {
background-color: #fff;
}
.estimator-table .parameters-table tr:nth-child(even) {
background-color: #f6f6f6;
}
.estimator-table .parameters-table tr:hover {
background-color: #e0e0e0;
}
.estimator-table table td {
border: 1px solid rgba(106, 105, 104, 0.232);
}
.user-set td {
color:rgb(255, 94, 0);
text-align: left;
}
.user-set td.value pre {
color:rgb(255, 94, 0) !important;
background-color: transparent !important;
}
.default td {
color: black;
text-align: left;
}
.user-set td i,
.default td i {
color: black;
}
.copy-paste-icon {
background-image: url(data:image/svg+xml;base64,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);
background-repeat: no-repeat;
background-size: 14px 14px;
background-position: 0;
display: inline-block;
width: 14px;
height: 14px;
cursor: pointer;
}
</style>
On GitHub, the HTML representation is unable to render, please try loading this page with nbviewer.org.
<script>function copyToClipboard(text, element) {
// Get the parameter prefix from the closest toggleable content
const toggleableContent = element.closest('.sk-toggleable__content');
const paramPrefix = toggleableContent ? toggleableContent.dataset.paramPrefix : '';
const fullParamName = paramPrefix ? `${paramPrefix}${text}` : text;
const originalStyle = element.style;
const computedStyle = window.getComputedStyle(element);
const originalWidth = computedStyle.width;
const originalHTML = element.innerHTML.replace('Copied!', '');
navigator.clipboard.writeText(fullParamName)
.then(() => {
element.style.width = originalWidth;
element.style.color = 'green';
element.innerHTML = "Copied!";
setTimeout(() => {
element.innerHTML = originalHTML;
element.style = originalStyle;
}, 2000);
})
.catch(err => {
console.error('Failed to copy:', err);
element.style.color = 'red';
element.innerHTML = "Failed!";
setTimeout(() => {
element.innerHTML = originalHTML;
element.style = originalStyle;
}, 2000);
});
return false;
}
document.querySelectorAll('.fa-regular.fa-copy').forEach(function(element) {
const toggleableContent = element.closest('.sk-toggleable__content');
const paramPrefix = toggleableContent ? toggleableContent.dataset.paramPrefix : '';
const paramName = element.parentElement.nextElementSibling.textContent.trim();
const fullParamName = paramPrefix ? `${paramPrefix}${paramName}` : paramName;
element.setAttribute('title', fullParamName);
});
</script>
KNeighborsClassifier(metric='euclidean', n_neighbors=3)In a Jupyter environment, please rerun this cell to show the HTML representation or trust the notebook.
On GitHub, the HTML representation is unable to render, please try loading this page with nbviewer.org.
Parameters
| n_neighbors | 3 | |
| weights | 'uniform' | |
| algorithm | 'auto' | |
| leaf_size | 30 | |
| p | 2 | |
| metric | 'euclidean' | |
| metric_params | None | |
| n_jobs | None |
prediction = knn.predict(X_test)print ('Prediction and test: ')
print (prediction)
print (y_test)Prediction and test:
[1 1 0 0 0 1 1 1 0 0 1 0 0 0 0 1 1 0 1 1 0 0 1 0 1 0 0 1 0 0 0 1 1 0 0 0 1
1 0 1 1 0 0 1 0 0 1 1 0 1 0 1 1 0 1 1 0 1 1 0 1 1 1 0 0 1 1 1 1 1 1 1 0 1
0 0 1 0 1 1 0 1 1 1 1 0 1 1 0 0 1 1 0 1 1 1 0 1 1 1 0 0 0 1 0 0 0 1 1 1 1
0 0 1 0 0 0 0 0 0 0 1 0 1 1 1 1 1 0 0 0 1 1 1 1 1 1 1 1 1 1 0 0 0 0 1 0 1
0 1 0 1 0 0 0 1 1 0 1 1 0 1 1 0 0 0 1 0 0 1 1 0 1 1 0 0 1 1 1 1 0 1 0 0 1
0 0 1 1 1 0 1 0 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 0 1 0 0 0 0 0 0
0 0 0 1 0 0 0 0 1 0 1 0 1 1 0 1 1 0 1 1 1 0 1 0 1 1 0 1]
[1 1 0 0 0 0 1 1 0 0 0 0 0 0 0 1 1 0 1 0 0 0 0 0 1 0 0 1 0 0 0 1 1 0 0 0 1
1 0 1 1 0 0 1 1 1 1 1 0 0 0 1 0 0 1 1 0 1 1 0 1 1 0 0 0 1 1 1 0 1 1 1 0 0
0 0 0 0 1 1 0 1 0 1 1 0 1 1 0 0 1 1 0 1 1 1 0 1 1 1 0 0 0 0 0 0 0 1 0 1 1
0 0 0 1 0 0 0 0 0 0 1 0 1 1 0 1 1 0 0 0 0 1 1 1 1 1 1 1 1 1 0 0 0 1 0 0 1
0 0 0 0 0 0 0 0 0 0 1 1 0 1 1 0 0 0 1 0 0 1 1 0 1 1 0 0 1 1 1 1 0 1 0 0 1
0 0 0 1 1 0 1 0 1 1 1 1 0 1 1 1 1 0 1 1 1 1 1 1 1 0 1 0 1 1 1 0 0 0 0 0 0
0 0 1 1 0 0 0 0 1 0 1 0 1 1 0 1 1 0 1 1 1 0 1 0 1 1 0 1]
print ('Confusion matrix: ')
print (confusion_matrix(y_test, prediction))Confusion matrix:
[[104 26]
[ 6 114]]
print ('Accuracy score: ', accuracy_score(prediction, y_test))Accuracy score: 0.872
print(classification_report(y_test, prediction)) precision recall f1-score support
0 0.95 0.80 0.87 130
1 0.81 0.95 0.88 120
accuracy 0.87 250
macro avg 0.88 0.88 0.87 250
weighted avg 0.88 0.87 0.87 250
roc_auc_score(y_test, prediction)0.875plt.xlabel("first feature")
plt.ylabel("second feature")
plot_2d_separator(knn, X, fill=True)
plt.scatter(X[:, 0], X[:, 1], c=y, s=70)<matplotlib.collections.PathCollection at 0x9906118>
#RS_9knn = KNeighborsClassifier(n_neighbors=9, metric = 'euclidean')knn.fit(X_train, y_train)
<style>#sk-container-id-3 {
/* Definition of color scheme common for light and dark mode */
--sklearn-color-text: #000;
--sklearn-color-text-muted: #666;
--sklearn-color-line: gray;
/* Definition of color scheme for unfitted estimators */
--sklearn-color-unfitted-level-0: #fff5e6;
--sklearn-color-unfitted-level-1: #f6e4d2;
--sklearn-color-unfitted-level-2: #ffe0b3;
--sklearn-color-unfitted-level-3: chocolate;
/* Definition of color scheme for fitted estimators */
--sklearn-color-fitted-level-0: #f0f8ff;
--sklearn-color-fitted-level-1: #d4ebff;
--sklearn-color-fitted-level-2: #b3dbfd;
--sklearn-color-fitted-level-3: cornflowerblue;
/* Specific color for light theme */
--sklearn-color-text-on-default-background: var(--sg-text-color, var(--theme-code-foreground, var(--jp-content-font-color1, black)));
--sklearn-color-background: var(--sg-background-color, var(--theme-background, var(--jp-layout-color0, white)));
--sklearn-color-border-box: var(--sg-text-color, var(--theme-code-foreground, var(--jp-content-font-color1, black)));
--sklearn-color-icon: #696969;
@media (prefers-color-scheme: dark) {
/* Redefinition of color scheme for dark theme */
--sklearn-color-text-on-default-background: var(--sg-text-color, var(--theme-code-foreground, var(--jp-content-font-color1, white)));
--sklearn-color-background: var(--sg-background-color, var(--theme-background, var(--jp-layout-color0, #111)));
--sklearn-color-border-box: var(--sg-text-color, var(--theme-code-foreground, var(--jp-content-font-color1, white)));
--sklearn-color-icon: #878787;
}
}
#sk-container-id-3 {
color: var(--sklearn-color-text);
}
#sk-container-id-3 pre {
padding: 0;
}
#sk-container-id-3 input.sk-hidden--visually {
border: 0;
clip: rect(1px 1px 1px 1px);
clip: rect(1px, 1px, 1px, 1px);
height: 1px;
margin: -1px;
overflow: hidden;
padding: 0;
position: absolute;
width: 1px;
}
#sk-container-id-3 div.sk-dashed-wrapped {
border: 1px dashed var(--sklearn-color-line);
margin: 0 0.4em 0.5em 0.4em;
box-sizing: border-box;
padding-bottom: 0.4em;
background-color: var(--sklearn-color-background);
}
#sk-container-id-3 div.sk-container {
/* jupyter's `normalize.less` sets `[hidden] { display: none; }`
but bootstrap.min.css set `[hidden] { display: none !important; }`
so we also need the `!important` here to be able to override the
default hidden behavior on the sphinx rendered scikit-learn.org.
See: https://github.com/scikit-learn/scikit-learn/issues/21755 */
display: inline-block !important;
position: relative;
}
#sk-container-id-3 div.sk-text-repr-fallback {
display: none;
}
div.sk-parallel-item,
div.sk-serial,
div.sk-item {
/* draw centered vertical line to link estimators */
background-image: linear-gradient(var(--sklearn-color-text-on-default-background), var(--sklearn-color-text-on-default-background));
background-size: 2px 100%;
background-repeat: no-repeat;
background-position: center center;
}
/* Parallel-specific style estimator block */
#sk-container-id-3 div.sk-parallel-item::after {
content: "";
width: 100%;
border-bottom: 2px solid var(--sklearn-color-text-on-default-background);
flex-grow: 1;
}
#sk-container-id-3 div.sk-parallel {
display: flex;
align-items: stretch;
justify-content: center;
background-color: var(--sklearn-color-background);
position: relative;
}
#sk-container-id-3 div.sk-parallel-item {
display: flex;
flex-direction: column;
}
#sk-container-id-3 div.sk-parallel-item:first-child::after {
align-self: flex-end;
width: 50%;
}
#sk-container-id-3 div.sk-parallel-item:last-child::after {
align-self: flex-start;
width: 50%;
}
#sk-container-id-3 div.sk-parallel-item:only-child::after {
width: 0;
}
/* Serial-specific style estimator block */
#sk-container-id-3 div.sk-serial {
display: flex;
flex-direction: column;
align-items: center;
background-color: var(--sklearn-color-background);
padding-right: 1em;
padding-left: 1em;
}
/* Toggleable style: style used for estimator/Pipeline/ColumnTransformer box that is
clickable and can be expanded/collapsed.
- Pipeline and ColumnTransformer use this feature and define the default style
- Estimators will overwrite some part of the style using the `sk-estimator` class
*/
/* Pipeline and ColumnTransformer style (default) */
#sk-container-id-3 div.sk-toggleable {
/* Default theme specific background. It is overwritten whether we have a
specific estimator or a Pipeline/ColumnTransformer */
background-color: var(--sklearn-color-background);
}
/* Toggleable label */
#sk-container-id-3 label.sk-toggleable__label {
cursor: pointer;
display: flex;
width: 100%;
margin-bottom: 0;
padding: 0.5em;
box-sizing: border-box;
text-align: center;
align-items: start;
justify-content: space-between;
gap: 0.5em;
}
#sk-container-id-3 label.sk-toggleable__label .caption {
font-size: 0.6rem;
font-weight: lighter;
color: var(--sklearn-color-text-muted);
}
#sk-container-id-3 label.sk-toggleable__label-arrow:before {
/* Arrow on the left of the label */
content: "▸";
float: left;
margin-right: 0.25em;
color: var(--sklearn-color-icon);
}
#sk-container-id-3 label.sk-toggleable__label-arrow:hover:before {
color: var(--sklearn-color-text);
}
/* Toggleable content - dropdown */
#sk-container-id-3 div.sk-toggleable__content {
display: none;
text-align: left;
/* unfitted */
background-color: var(--sklearn-color-unfitted-level-0);
}
#sk-container-id-3 div.sk-toggleable__content.fitted {
/* fitted */
background-color: var(--sklearn-color-fitted-level-0);
}
#sk-container-id-3 div.sk-toggleable__content pre {
margin: 0.2em;
border-radius: 0.25em;
color: var(--sklearn-color-text);
/* unfitted */
background-color: var(--sklearn-color-unfitted-level-0);
}
#sk-container-id-3 div.sk-toggleable__content.fitted pre {
/* unfitted */
background-color: var(--sklearn-color-fitted-level-0);
}
#sk-container-id-3 input.sk-toggleable__control:checked~div.sk-toggleable__content {
/* Expand drop-down */
display: block;
width: 100%;
overflow: visible;
}
#sk-container-id-3 input.sk-toggleable__control:checked~label.sk-toggleable__label-arrow:before {
content: "▾";
}
/* Pipeline/ColumnTransformer-specific style */
#sk-container-id-3 div.sk-label input.sk-toggleable__control:checked~label.sk-toggleable__label {
color: var(--sklearn-color-text);
background-color: var(--sklearn-color-unfitted-level-2);
}
#sk-container-id-3 div.sk-label.fitted input.sk-toggleable__control:checked~label.sk-toggleable__label {
background-color: var(--sklearn-color-fitted-level-2);
}
/* Estimator-specific style */
/* Colorize estimator box */
#sk-container-id-3 div.sk-estimator input.sk-toggleable__control:checked~label.sk-toggleable__label {
/* unfitted */
background-color: var(--sklearn-color-unfitted-level-2);
}
#sk-container-id-3 div.sk-estimator.fitted input.sk-toggleable__control:checked~label.sk-toggleable__label {
/* fitted */
background-color: var(--sklearn-color-fitted-level-2);
}
#sk-container-id-3 div.sk-label label.sk-toggleable__label,
#sk-container-id-3 div.sk-label label {
/* The background is the default theme color */
color: var(--sklearn-color-text-on-default-background);
}
/* On hover, darken the color of the background */
#sk-container-id-3 div.sk-label:hover label.sk-toggleable__label {
color: var(--sklearn-color-text);
background-color: var(--sklearn-color-unfitted-level-2);
}
/* Label box, darken color on hover, fitted */
#sk-container-id-3 div.sk-label.fitted:hover label.sk-toggleable__label.fitted {
color: var(--sklearn-color-text);
background-color: var(--sklearn-color-fitted-level-2);
}
/* Estimator label */
#sk-container-id-3 div.sk-label label {
font-family: monospace;
font-weight: bold;
display: inline-block;
line-height: 1.2em;
}
#sk-container-id-3 div.sk-label-container {
text-align: center;
}
/* Estimator-specific */
#sk-container-id-3 div.sk-estimator {
font-family: monospace;
border: 1px dotted var(--sklearn-color-border-box);
border-radius: 0.25em;
box-sizing: border-box;
margin-bottom: 0.5em;
/* unfitted */
background-color: var(--sklearn-color-unfitted-level-0);
}
#sk-container-id-3 div.sk-estimator.fitted {
/* fitted */
background-color: var(--sklearn-color-fitted-level-0);
}
/* on hover */
#sk-container-id-3 div.sk-estimator:hover {
/* unfitted */
background-color: var(--sklearn-color-unfitted-level-2);
}
#sk-container-id-3 div.sk-estimator.fitted:hover {
/* fitted */
background-color: var(--sklearn-color-fitted-level-2);
}
/* Specification for estimator info (e.g. "i" and "?") */
/* Common style for "i" and "?" */
.sk-estimator-doc-link,
a:link.sk-estimator-doc-link,
a:visited.sk-estimator-doc-link {
float: right;
font-size: smaller;
line-height: 1em;
font-family: monospace;
background-color: var(--sklearn-color-background);
border-radius: 1em;
height: 1em;
width: 1em;
text-decoration: none !important;
margin-left: 0.5em;
text-align: center;
/* unfitted */
border: var(--sklearn-color-unfitted-level-1) 1pt solid;
color: var(--sklearn-color-unfitted-level-1);
}
.sk-estimator-doc-link.fitted,
a:link.sk-estimator-doc-link.fitted,
a:visited.sk-estimator-doc-link.fitted {
/* fitted */
border: var(--sklearn-color-fitted-level-1) 1pt solid;
color: var(--sklearn-color-fitted-level-1);
}
/* On hover */
div.sk-estimator:hover .sk-estimator-doc-link:hover,
.sk-estimator-doc-link:hover,
div.sk-label-container:hover .sk-estimator-doc-link:hover,
.sk-estimator-doc-link:hover {
/* unfitted */
background-color: var(--sklearn-color-unfitted-level-3);
color: var(--sklearn-color-background);
text-decoration: none;
}
div.sk-estimator.fitted:hover .sk-estimator-doc-link.fitted:hover,
.sk-estimator-doc-link.fitted:hover,
div.sk-label-container:hover .sk-estimator-doc-link.fitted:hover,
.sk-estimator-doc-link.fitted:hover {
/* fitted */
background-color: var(--sklearn-color-fitted-level-3);
color: var(--sklearn-color-background);
text-decoration: none;
}
/* Span, style for the box shown on hovering the info icon */
.sk-estimator-doc-link span {
display: none;
z-index: 9999;
position: relative;
font-weight: normal;
right: .2ex;
padding: .5ex;
margin: .5ex;
width: min-content;
min-width: 20ex;
max-width: 50ex;
color: var(--sklearn-color-text);
box-shadow: 2pt 2pt 4pt #999;
/* unfitted */
background: var(--sklearn-color-unfitted-level-0);
border: .5pt solid var(--sklearn-color-unfitted-level-3);
}
.sk-estimator-doc-link.fitted span {
/* fitted */
background: var(--sklearn-color-fitted-level-0);
border: var(--sklearn-color-fitted-level-3);
}
.sk-estimator-doc-link:hover span {
display: block;
}
/* "?"-specific style due to the `` HTML tag */
#sk-container-id-3 a.estimator_doc_link {
float: right;
font-size: 1rem;
line-height: 1em;
font-family: monospace;
background-color: var(--sklearn-color-background);
border-radius: 1rem;
height: 1rem;
width: 1rem;
text-decoration: none;
/* unfitted */
color: var(--sklearn-color-unfitted-level-1);
border: var(--sklearn-color-unfitted-level-1) 1pt solid;
}
#sk-container-id-3 a.estimator_doc_link.fitted {
/* fitted */
border: var(--sklearn-color-fitted-level-1) 1pt solid;
color: var(--sklearn-color-fitted-level-1);
}
/* On hover */
#sk-container-id-3 a.estimator_doc_link:hover {
/* unfitted */
background-color: var(--sklearn-color-unfitted-level-3);
color: var(--sklearn-color-background);
text-decoration: none;
}
#sk-container-id-3 a.estimator_doc_link.fitted:hover {
/* fitted */
background-color: var(--sklearn-color-fitted-level-3);
}
.estimator-table summary {
padding: .5rem;
font-family: monospace;
cursor: pointer;
}
.estimator-table details[open] {
padding-left: 0.1rem;
padding-right: 0.1rem;
padding-bottom: 0.3rem;
}
.estimator-table .parameters-table {
margin-left: auto !important;
margin-right: auto !important;
}
.estimator-table .parameters-table tr:nth-child(odd) {
background-color: #fff;
}
.estimator-table .parameters-table tr:nth-child(even) {
background-color: #f6f6f6;
}
.estimator-table .parameters-table tr:hover {
background-color: #e0e0e0;
}
.estimator-table table td {
border: 1px solid rgba(106, 105, 104, 0.232);
}
.user-set td {
color:rgb(255, 94, 0);
text-align: left;
}
.user-set td.value pre {
color:rgb(255, 94, 0) !important;
background-color: transparent !important;
}
.default td {
color: black;
text-align: left;
}
.user-set td i,
.default td i {
color: black;
}
.copy-paste-icon {
background-image: url(data:image/svg+xml;base64,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);
background-repeat: no-repeat;
background-size: 14px 14px;
background-position: 0;
display: inline-block;
width: 14px;
height: 14px;
cursor: pointer;
}
</style>
On GitHub, the HTML representation is unable to render, please try loading this page with nbviewer.org.
<script>function copyToClipboard(text, element) {
// Get the parameter prefix from the closest toggleable content
const toggleableContent = element.closest('.sk-toggleable__content');
const paramPrefix = toggleableContent ? toggleableContent.dataset.paramPrefix : '';
const fullParamName = paramPrefix ? `${paramPrefix}${text}` : text;
const originalStyle = element.style;
const computedStyle = window.getComputedStyle(element);
const originalWidth = computedStyle.width;
const originalHTML = element.innerHTML.replace('Copied!', '');
navigator.clipboard.writeText(fullParamName)
.then(() => {
element.style.width = originalWidth;
element.style.color = 'green';
element.innerHTML = "Copied!";
setTimeout(() => {
element.innerHTML = originalHTML;
element.style = originalStyle;
}, 2000);
})
.catch(err => {
console.error('Failed to copy:', err);
element.style.color = 'red';
element.innerHTML = "Failed!";
setTimeout(() => {
element.innerHTML = originalHTML;
element.style = originalStyle;
}, 2000);
});
return false;
}
document.querySelectorAll('.fa-regular.fa-copy').forEach(function(element) {
const toggleableContent = element.closest('.sk-toggleable__content');
const paramPrefix = toggleableContent ? toggleableContent.dataset.paramPrefix : '';
const paramName = element.parentElement.nextElementSibling.textContent.trim();
const fullParamName = paramPrefix ? `${paramPrefix}${paramName}` : paramName;
element.setAttribute('title', fullParamName);
});
</script>
KNeighborsClassifier(metric='euclidean', n_neighbors=9)In a Jupyter environment, please rerun this cell to show the HTML representation or trust the notebook.
On GitHub, the HTML representation is unable to render, please try loading this page with nbviewer.org.
Parameters
| n_neighbors | 9 | |
| weights | 'uniform' | |
| algorithm | 'auto' | |
| leaf_size | 30 | |
| p | 2 | |
| metric | 'euclidean' | |
| metric_params | None | |
| n_jobs | None |
prediction = knn.predict(X_test)print ('Prediction and test: ')
print (prediction)
print (y_test)Prediction and test:
[1 1 1 0 0 1 1 1 0 0 1 0 0 0 0 1 1 0 1 1 0 0 1 0 1 0 0 1 0 0 0 1 1 0 0 0 1
1 0 1 1 0 0 1 1 1 1 1 0 1 0 1 1 0 1 1 0 1 1 1 1 1 1 0 0 1 1 1 1 1 1 0 0 1
0 0 1 0 1 1 0 1 1 1 1 0 1 1 0 0 1 1 1 1 1 1 0 1 1 1 0 0 0 1 0 0 0 1 1 1 1
0 0 1 1 0 0 0 0 0 0 1 0 1 1 1 1 1 0 0 0 1 1 1 1 0 1 1 1 1 1 0 0 0 1 1 0 1
0 1 0 1 0 0 0 1 1 0 1 1 0 1 1 0 0 0 1 0 0 1 1 0 1 1 0 0 1 1 1 1 0 1 0 0 1
0 0 1 1 1 0 1 0 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 0 1 0 1 0 0 0 0 1 0
0 0 1 1 0 0 0 0 1 0 1 0 1 1 0 1 1 0 1 1 1 1 1 0 1 1 0 1]
[1 1 0 0 0 0 1 1 0 0 0 0 0 0 0 1 1 0 1 0 0 0 0 0 1 0 0 1 0 0 0 1 1 0 0 0 1
1 0 1 1 0 0 1 1 1 1 1 0 0 0 1 0 0 1 1 0 1 1 0 1 1 0 0 0 1 1 1 0 1 1 1 0 0
0 0 0 0 1 1 0 1 0 1 1 0 1 1 0 0 1 1 0 1 1 1 0 1 1 1 0 0 0 0 0 0 0 1 0 1 1
0 0 0 1 0 0 0 0 0 0 1 0 1 1 0 1 1 0 0 0 0 1 1 1 1 1 1 1 1 1 0 0 0 1 0 0 1
0 0 0 0 0 0 0 0 0 0 1 1 0 1 1 0 0 0 1 0 0 1 1 0 1 1 0 0 1 1 1 1 0 1 0 0 1
0 0 0 1 1 0 1 0 1 1 1 1 0 1 1 1 1 0 1 1 1 1 1 1 1 0 1 0 1 1 1 0 0 0 0 0 0
0 0 1 1 0 0 0 0 1 0 1 0 1 1 0 1 1 0 1 1 1 0 1 0 1 1 0 1]
print ('Confusion matrix: ')
print (confusion_matrix(y_test, prediction))Confusion matrix:
[[100 30]
[ 3 117]]
print ('Accuracy score: ', accuracy_score(prediction, y_test))Accuracy score: 0.868
print(classification_report(y_test, prediction)) precision recall f1-score support
0 0.97 0.77 0.86 130
1 0.80 0.97 0.88 120
accuracy 0.87 250
macro avg 0.88 0.87 0.87 250
weighted avg 0.89 0.87 0.87 250
roc_auc_score(y_test, prediction)0.8721153846153846plt.xlabel("first feature")
plt.ylabel("second feature")
plot_2d_separator(knn, X, fill=True)
plt.scatter(X[:, 0], X[:, 1], c=y, s=70)<matplotlib.collections.PathCollection at 0x953b1f0>
#GaussianNBfrom sklearn.naive_bayes import GaussianNBgnb=GaussianNB()gnb.fit(X_train, y_train)
<style>#sk-container-id-4 {
/* Definition of color scheme common for light and dark mode */
--sklearn-color-text: #000;
--sklearn-color-text-muted: #666;
--sklearn-color-line: gray;
/* Definition of color scheme for unfitted estimators */
--sklearn-color-unfitted-level-0: #fff5e6;
--sklearn-color-unfitted-level-1: #f6e4d2;
--sklearn-color-unfitted-level-2: #ffe0b3;
--sklearn-color-unfitted-level-3: chocolate;
/* Definition of color scheme for fitted estimators */
--sklearn-color-fitted-level-0: #f0f8ff;
--sklearn-color-fitted-level-1: #d4ebff;
--sklearn-color-fitted-level-2: #b3dbfd;
--sklearn-color-fitted-level-3: cornflowerblue;
/* Specific color for light theme */
--sklearn-color-text-on-default-background: var(--sg-text-color, var(--theme-code-foreground, var(--jp-content-font-color1, black)));
--sklearn-color-background: var(--sg-background-color, var(--theme-background, var(--jp-layout-color0, white)));
--sklearn-color-border-box: var(--sg-text-color, var(--theme-code-foreground, var(--jp-content-font-color1, black)));
--sklearn-color-icon: #696969;
@media (prefers-color-scheme: dark) {
/* Redefinition of color scheme for dark theme */
--sklearn-color-text-on-default-background: var(--sg-text-color, var(--theme-code-foreground, var(--jp-content-font-color1, white)));
--sklearn-color-background: var(--sg-background-color, var(--theme-background, var(--jp-layout-color0, #111)));
--sklearn-color-border-box: var(--sg-text-color, var(--theme-code-foreground, var(--jp-content-font-color1, white)));
--sklearn-color-icon: #878787;
}
}
#sk-container-id-4 {
color: var(--sklearn-color-text);
}
#sk-container-id-4 pre {
padding: 0;
}
#sk-container-id-4 input.sk-hidden--visually {
border: 0;
clip: rect(1px 1px 1px 1px);
clip: rect(1px, 1px, 1px, 1px);
height: 1px;
margin: -1px;
overflow: hidden;
padding: 0;
position: absolute;
width: 1px;
}
#sk-container-id-4 div.sk-dashed-wrapped {
border: 1px dashed var(--sklearn-color-line);
margin: 0 0.4em 0.5em 0.4em;
box-sizing: border-box;
padding-bottom: 0.4em;
background-color: var(--sklearn-color-background);
}
#sk-container-id-4 div.sk-container {
/* jupyter's `normalize.less` sets `[hidden] { display: none; }`
but bootstrap.min.css set `[hidden] { display: none !important; }`
so we also need the `!important` here to be able to override the
default hidden behavior on the sphinx rendered scikit-learn.org.
See: https://github.com/scikit-learn/scikit-learn/issues/21755 */
display: inline-block !important;
position: relative;
}
#sk-container-id-4 div.sk-text-repr-fallback {
display: none;
}
div.sk-parallel-item,
div.sk-serial,
div.sk-item {
/* draw centered vertical line to link estimators */
background-image: linear-gradient(var(--sklearn-color-text-on-default-background), var(--sklearn-color-text-on-default-background));
background-size: 2px 100%;
background-repeat: no-repeat;
background-position: center center;
}
/* Parallel-specific style estimator block */
#sk-container-id-4 div.sk-parallel-item::after {
content: "";
width: 100%;
border-bottom: 2px solid var(--sklearn-color-text-on-default-background);
flex-grow: 1;
}
#sk-container-id-4 div.sk-parallel {
display: flex;
align-items: stretch;
justify-content: center;
background-color: var(--sklearn-color-background);
position: relative;
}
#sk-container-id-4 div.sk-parallel-item {
display: flex;
flex-direction: column;
}
#sk-container-id-4 div.sk-parallel-item:first-child::after {
align-self: flex-end;
width: 50%;
}
#sk-container-id-4 div.sk-parallel-item:last-child::after {
align-self: flex-start;
width: 50%;
}
#sk-container-id-4 div.sk-parallel-item:only-child::after {
width: 0;
}
/* Serial-specific style estimator block */
#sk-container-id-4 div.sk-serial {
display: flex;
flex-direction: column;
align-items: center;
background-color: var(--sklearn-color-background);
padding-right: 1em;
padding-left: 1em;
}
/* Toggleable style: style used for estimator/Pipeline/ColumnTransformer box that is
clickable and can be expanded/collapsed.
- Pipeline and ColumnTransformer use this feature and define the default style
- Estimators will overwrite some part of the style using the `sk-estimator` class
*/
/* Pipeline and ColumnTransformer style (default) */
#sk-container-id-4 div.sk-toggleable {
/* Default theme specific background. It is overwritten whether we have a
specific estimator or a Pipeline/ColumnTransformer */
background-color: var(--sklearn-color-background);
}
/* Toggleable label */
#sk-container-id-4 label.sk-toggleable__label {
cursor: pointer;
display: flex;
width: 100%;
margin-bottom: 0;
padding: 0.5em;
box-sizing: border-box;
text-align: center;
align-items: start;
justify-content: space-between;
gap: 0.5em;
}
#sk-container-id-4 label.sk-toggleable__label .caption {
font-size: 0.6rem;
font-weight: lighter;
color: var(--sklearn-color-text-muted);
}
#sk-container-id-4 label.sk-toggleable__label-arrow:before {
/* Arrow on the left of the label */
content: "▸";
float: left;
margin-right: 0.25em;
color: var(--sklearn-color-icon);
}
#sk-container-id-4 label.sk-toggleable__label-arrow:hover:before {
color: var(--sklearn-color-text);
}
/* Toggleable content - dropdown */
#sk-container-id-4 div.sk-toggleable__content {
display: none;
text-align: left;
/* unfitted */
background-color: var(--sklearn-color-unfitted-level-0);
}
#sk-container-id-4 div.sk-toggleable__content.fitted {
/* fitted */
background-color: var(--sklearn-color-fitted-level-0);
}
#sk-container-id-4 div.sk-toggleable__content pre {
margin: 0.2em;
border-radius: 0.25em;
color: var(--sklearn-color-text);
/* unfitted */
background-color: var(--sklearn-color-unfitted-level-0);
}
#sk-container-id-4 div.sk-toggleable__content.fitted pre {
/* unfitted */
background-color: var(--sklearn-color-fitted-level-0);
}
#sk-container-id-4 input.sk-toggleable__control:checked~div.sk-toggleable__content {
/* Expand drop-down */
display: block;
width: 100%;
overflow: visible;
}
#sk-container-id-4 input.sk-toggleable__control:checked~label.sk-toggleable__label-arrow:before {
content: "▾";
}
/* Pipeline/ColumnTransformer-specific style */
#sk-container-id-4 div.sk-label input.sk-toggleable__control:checked~label.sk-toggleable__label {
color: var(--sklearn-color-text);
background-color: var(--sklearn-color-unfitted-level-2);
}
#sk-container-id-4 div.sk-label.fitted input.sk-toggleable__control:checked~label.sk-toggleable__label {
background-color: var(--sklearn-color-fitted-level-2);
}
/* Estimator-specific style */
/* Colorize estimator box */
#sk-container-id-4 div.sk-estimator input.sk-toggleable__control:checked~label.sk-toggleable__label {
/* unfitted */
background-color: var(--sklearn-color-unfitted-level-2);
}
#sk-container-id-4 div.sk-estimator.fitted input.sk-toggleable__control:checked~label.sk-toggleable__label {
/* fitted */
background-color: var(--sklearn-color-fitted-level-2);
}
#sk-container-id-4 div.sk-label label.sk-toggleable__label,
#sk-container-id-4 div.sk-label label {
/* The background is the default theme color */
color: var(--sklearn-color-text-on-default-background);
}
/* On hover, darken the color of the background */
#sk-container-id-4 div.sk-label:hover label.sk-toggleable__label {
color: var(--sklearn-color-text);
background-color: var(--sklearn-color-unfitted-level-2);
}
/* Label box, darken color on hover, fitted */
#sk-container-id-4 div.sk-label.fitted:hover label.sk-toggleable__label.fitted {
color: var(--sklearn-color-text);
background-color: var(--sklearn-color-fitted-level-2);
}
/* Estimator label */
#sk-container-id-4 div.sk-label label {
font-family: monospace;
font-weight: bold;
display: inline-block;
line-height: 1.2em;
}
#sk-container-id-4 div.sk-label-container {
text-align: center;
}
/* Estimator-specific */
#sk-container-id-4 div.sk-estimator {
font-family: monospace;
border: 1px dotted var(--sklearn-color-border-box);
border-radius: 0.25em;
box-sizing: border-box;
margin-bottom: 0.5em;
/* unfitted */
background-color: var(--sklearn-color-unfitted-level-0);
}
#sk-container-id-4 div.sk-estimator.fitted {
/* fitted */
background-color: var(--sklearn-color-fitted-level-0);
}
/* on hover */
#sk-container-id-4 div.sk-estimator:hover {
/* unfitted */
background-color: var(--sklearn-color-unfitted-level-2);
}
#sk-container-id-4 div.sk-estimator.fitted:hover {
/* fitted */
background-color: var(--sklearn-color-fitted-level-2);
}
/* Specification for estimator info (e.g. "i" and "?") */
/* Common style for "i" and "?" */
.sk-estimator-doc-link,
a:link.sk-estimator-doc-link,
a:visited.sk-estimator-doc-link {
float: right;
font-size: smaller;
line-height: 1em;
font-family: monospace;
background-color: var(--sklearn-color-background);
border-radius: 1em;
height: 1em;
width: 1em;
text-decoration: none !important;
margin-left: 0.5em;
text-align: center;
/* unfitted */
border: var(--sklearn-color-unfitted-level-1) 1pt solid;
color: var(--sklearn-color-unfitted-level-1);
}
.sk-estimator-doc-link.fitted,
a:link.sk-estimator-doc-link.fitted,
a:visited.sk-estimator-doc-link.fitted {
/* fitted */
border: var(--sklearn-color-fitted-level-1) 1pt solid;
color: var(--sklearn-color-fitted-level-1);
}
/* On hover */
div.sk-estimator:hover .sk-estimator-doc-link:hover,
.sk-estimator-doc-link:hover,
div.sk-label-container:hover .sk-estimator-doc-link:hover,
.sk-estimator-doc-link:hover {
/* unfitted */
background-color: var(--sklearn-color-unfitted-level-3);
color: var(--sklearn-color-background);
text-decoration: none;
}
div.sk-estimator.fitted:hover .sk-estimator-doc-link.fitted:hover,
.sk-estimator-doc-link.fitted:hover,
div.sk-label-container:hover .sk-estimator-doc-link.fitted:hover,
.sk-estimator-doc-link.fitted:hover {
/* fitted */
background-color: var(--sklearn-color-fitted-level-3);
color: var(--sklearn-color-background);
text-decoration: none;
}
/* Span, style for the box shown on hovering the info icon */
.sk-estimator-doc-link span {
display: none;
z-index: 9999;
position: relative;
font-weight: normal;
right: .2ex;
padding: .5ex;
margin: .5ex;
width: min-content;
min-width: 20ex;
max-width: 50ex;
color: var(--sklearn-color-text);
box-shadow: 2pt 2pt 4pt #999;
/* unfitted */
background: var(--sklearn-color-unfitted-level-0);
border: .5pt solid var(--sklearn-color-unfitted-level-3);
}
.sk-estimator-doc-link.fitted span {
/* fitted */
background: var(--sklearn-color-fitted-level-0);
border: var(--sklearn-color-fitted-level-3);
}
.sk-estimator-doc-link:hover span {
display: block;
}
/* "?"-specific style due to the `` HTML tag */
#sk-container-id-4 a.estimator_doc_link {
float: right;
font-size: 1rem;
line-height: 1em;
font-family: monospace;
background-color: var(--sklearn-color-background);
border-radius: 1rem;
height: 1rem;
width: 1rem;
text-decoration: none;
/* unfitted */
color: var(--sklearn-color-unfitted-level-1);
border: var(--sklearn-color-unfitted-level-1) 1pt solid;
}
#sk-container-id-4 a.estimator_doc_link.fitted {
/* fitted */
border: var(--sklearn-color-fitted-level-1) 1pt solid;
color: var(--sklearn-color-fitted-level-1);
}
/* On hover */
#sk-container-id-4 a.estimator_doc_link:hover {
/* unfitted */
background-color: var(--sklearn-color-unfitted-level-3);
color: var(--sklearn-color-background);
text-decoration: none;
}
#sk-container-id-4 a.estimator_doc_link.fitted:hover {
/* fitted */
background-color: var(--sklearn-color-fitted-level-3);
}
.estimator-table summary {
padding: .5rem;
font-family: monospace;
cursor: pointer;
}
.estimator-table details[open] {
padding-left: 0.1rem;
padding-right: 0.1rem;
padding-bottom: 0.3rem;
}
.estimator-table .parameters-table {
margin-left: auto !important;
margin-right: auto !important;
}
.estimator-table .parameters-table tr:nth-child(odd) {
background-color: #fff;
}
.estimator-table .parameters-table tr:nth-child(even) {
background-color: #f6f6f6;
}
.estimator-table .parameters-table tr:hover {
background-color: #e0e0e0;
}
.estimator-table table td {
border: 1px solid rgba(106, 105, 104, 0.232);
}
.user-set td {
color:rgb(255, 94, 0);
text-align: left;
}
.user-set td.value pre {
color:rgb(255, 94, 0) !important;
background-color: transparent !important;
}
.default td {
color: black;
text-align: left;
}
.user-set td i,
.default td i {
color: black;
}
.copy-paste-icon {
background-image: url(data:image/svg+xml;base64,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);
background-repeat: no-repeat;
background-size: 14px 14px;
background-position: 0;
display: inline-block;
width: 14px;
height: 14px;
cursor: pointer;
}
</style>
On GitHub, the HTML representation is unable to render, please try loading this page with nbviewer.org.
<script>function copyToClipboard(text, element) {
// Get the parameter prefix from the closest toggleable content
const toggleableContent = element.closest('.sk-toggleable__content');
const paramPrefix = toggleableContent ? toggleableContent.dataset.paramPrefix : '';
const fullParamName = paramPrefix ? `${paramPrefix}${text}` : text;
const originalStyle = element.style;
const computedStyle = window.getComputedStyle(element);
const originalWidth = computedStyle.width;
const originalHTML = element.innerHTML.replace('Copied!', '');
navigator.clipboard.writeText(fullParamName)
.then(() => {
element.style.width = originalWidth;
element.style.color = 'green';
element.innerHTML = "Copied!";
setTimeout(() => {
element.innerHTML = originalHTML;
element.style = originalStyle;
}, 2000);
})
.catch(err => {
console.error('Failed to copy:', err);
element.style.color = 'red';
element.innerHTML = "Failed!";
setTimeout(() => {
element.innerHTML = originalHTML;
element.style = originalStyle;
}, 2000);
});
return false;
}
document.querySelectorAll('.fa-regular.fa-copy').forEach(function(element) {
const toggleableContent = element.closest('.sk-toggleable__content');
const paramPrefix = toggleableContent ? toggleableContent.dataset.paramPrefix : '';
const paramName = element.parentElement.nextElementSibling.textContent.trim();
const fullParamName = paramPrefix ? `${paramPrefix}${paramName}` : paramName;
element.setAttribute('title', fullParamName);
});
</script>
GaussianNB()In a Jupyter environment, please rerun this cell to show the HTML representation or trust the notebook.
On GitHub, the HTML representation is unable to render, please try loading this page with nbviewer.org.
Parameters
| priors | None | |
| var_smoothing | 1e-09 |
prediction = gnb.predict(X_test)print ('Prediction and test: ')
print (prediction)
print (y_test)Prediction and test:
[1 1 0 0 0 1 1 1 0 0 1 0 0 0 0 1 1 0 1 0 0 0 1 0 1 0 0 1 0 0 0 1 1 0 0 0 1
1 0 1 1 0 0 1 1 1 1 1 0 1 0 1 1 0 1 1 0 1 1 1 1 1 1 0 0 1 1 1 0 1 1 1 0 1
0 0 1 0 1 1 0 1 1 1 1 0 1 1 0 0 1 1 1 1 1 1 0 1 1 1 0 0 0 1 0 0 0 1 1 1 1
0 0 0 1 0 0 0 0 0 0 1 0 1 1 1 1 1 0 0 0 1 1 1 1 1 1 1 1 1 1 0 0 0 1 1 0 1
0 1 0 0 0 0 0 1 1 0 1 1 0 1 1 0 0 0 1 0 0 1 1 0 1 1 0 0 1 1 1 1 0 1 0 0 1
0 0 1 1 1 0 1 0 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 0 1 0 1 0 0 0 0 0 0
0 0 1 1 0 0 0 0 1 0 1 0 1 1 0 1 1 0 1 1 1 0 1 0 1 1 0 1]
[1 1 0 0 0 0 1 1 0 0 0 0 0 0 0 1 1 0 1 0 0 0 0 0 1 0 0 1 0 0 0 1 1 0 0 0 1
1 0 1 1 0 0 1 1 1 1 1 0 0 0 1 0 0 1 1 0 1 1 0 1 1 0 0 0 1 1 1 0 1 1 1 0 0
0 0 0 0 1 1 0 1 0 1 1 0 1 1 0 0 1 1 0 1 1 1 0 1 1 1 0 0 0 0 0 0 0 1 0 1 1
0 0 0 1 0 0 0 0 0 0 1 0 1 1 0 1 1 0 0 0 0 1 1 1 1 1 1 1 1 1 0 0 0 1 0 0 1
0 0 0 0 0 0 0 0 0 0 1 1 0 1 1 0 0 0 1 0 0 1 1 0 1 1 0 0 1 1 1 1 0 1 0 0 1
0 0 0 1 1 0 1 0 1 1 1 1 0 1 1 1 1 0 1 1 1 1 1 1 1 0 1 0 1 1 1 0 0 0 0 0 0
0 0 1 1 0 0 0 0 1 0 1 0 1 1 0 1 1 0 1 1 1 0 1 0 1 1 0 1]
print ('Confusion matrix: ')
print (confusion_matrix(y_test, prediction))Confusion matrix:
[[107 23]
[ 1 119]]
print ('Accuracy score: ', accuracy_score(prediction, y_test))Accuracy score: 0.904
print(classification_report(y_test, prediction)) precision recall f1-score support
0 0.99 0.82 0.90 130
1 0.84 0.99 0.91 120
accuracy 0.90 250
macro avg 0.91 0.91 0.90 250
weighted avg 0.92 0.90 0.90 250
roc_auc_score(y_test, prediction)0.9073717948717948plt.xlabel("first feature")
plt.ylabel("second feature")
plot_2d_separator(gnb, X, fill=True)
plt.scatter(X[:, 0], X[:, 1], c=y, s=70)<matplotlib.collections.PathCollection at 0x9753278>
#RandFor-5from sklearn.ensemble import RandomForestClassifierrf=RandomForestClassifier(n_estimators=5,random_state=42)rf.fit(X_train, y_train)
<style>#sk-container-id-5 {
/* Definition of color scheme common for light and dark mode */
--sklearn-color-text: #000;
--sklearn-color-text-muted: #666;
--sklearn-color-line: gray;
/* Definition of color scheme for unfitted estimators */
--sklearn-color-unfitted-level-0: #fff5e6;
--sklearn-color-unfitted-level-1: #f6e4d2;
--sklearn-color-unfitted-level-2: #ffe0b3;
--sklearn-color-unfitted-level-3: chocolate;
/* Definition of color scheme for fitted estimators */
--sklearn-color-fitted-level-0: #f0f8ff;
--sklearn-color-fitted-level-1: #d4ebff;
--sklearn-color-fitted-level-2: #b3dbfd;
--sklearn-color-fitted-level-3: cornflowerblue;
/* Specific color for light theme */
--sklearn-color-text-on-default-background: var(--sg-text-color, var(--theme-code-foreground, var(--jp-content-font-color1, black)));
--sklearn-color-background: var(--sg-background-color, var(--theme-background, var(--jp-layout-color0, white)));
--sklearn-color-border-box: var(--sg-text-color, var(--theme-code-foreground, var(--jp-content-font-color1, black)));
--sklearn-color-icon: #696969;
@media (prefers-color-scheme: dark) {
/* Redefinition of color scheme for dark theme */
--sklearn-color-text-on-default-background: var(--sg-text-color, var(--theme-code-foreground, var(--jp-content-font-color1, white)));
--sklearn-color-background: var(--sg-background-color, var(--theme-background, var(--jp-layout-color0, #111)));
--sklearn-color-border-box: var(--sg-text-color, var(--theme-code-foreground, var(--jp-content-font-color1, white)));
--sklearn-color-icon: #878787;
}
}
#sk-container-id-5 {
color: var(--sklearn-color-text);
}
#sk-container-id-5 pre {
padding: 0;
}
#sk-container-id-5 input.sk-hidden--visually {
border: 0;
clip: rect(1px 1px 1px 1px);
clip: rect(1px, 1px, 1px, 1px);
height: 1px;
margin: -1px;
overflow: hidden;
padding: 0;
position: absolute;
width: 1px;
}
#sk-container-id-5 div.sk-dashed-wrapped {
border: 1px dashed var(--sklearn-color-line);
margin: 0 0.4em 0.5em 0.4em;
box-sizing: border-box;
padding-bottom: 0.4em;
background-color: var(--sklearn-color-background);
}
#sk-container-id-5 div.sk-container {
/* jupyter's `normalize.less` sets `[hidden] { display: none; }`
but bootstrap.min.css set `[hidden] { display: none !important; }`
so we also need the `!important` here to be able to override the
default hidden behavior on the sphinx rendered scikit-learn.org.
See: https://github.com/scikit-learn/scikit-learn/issues/21755 */
display: inline-block !important;
position: relative;
}
#sk-container-id-5 div.sk-text-repr-fallback {
display: none;
}
div.sk-parallel-item,
div.sk-serial,
div.sk-item {
/* draw centered vertical line to link estimators */
background-image: linear-gradient(var(--sklearn-color-text-on-default-background), var(--sklearn-color-text-on-default-background));
background-size: 2px 100%;
background-repeat: no-repeat;
background-position: center center;
}
/* Parallel-specific style estimator block */
#sk-container-id-5 div.sk-parallel-item::after {
content: "";
width: 100%;
border-bottom: 2px solid var(--sklearn-color-text-on-default-background);
flex-grow: 1;
}
#sk-container-id-5 div.sk-parallel {
display: flex;
align-items: stretch;
justify-content: center;
background-color: var(--sklearn-color-background);
position: relative;
}
#sk-container-id-5 div.sk-parallel-item {
display: flex;
flex-direction: column;
}
#sk-container-id-5 div.sk-parallel-item:first-child::after {
align-self: flex-end;
width: 50%;
}
#sk-container-id-5 div.sk-parallel-item:last-child::after {
align-self: flex-start;
width: 50%;
}
#sk-container-id-5 div.sk-parallel-item:only-child::after {
width: 0;
}
/* Serial-specific style estimator block */
#sk-container-id-5 div.sk-serial {
display: flex;
flex-direction: column;
align-items: center;
background-color: var(--sklearn-color-background);
padding-right: 1em;
padding-left: 1em;
}
/* Toggleable style: style used for estimator/Pipeline/ColumnTransformer box that is
clickable and can be expanded/collapsed.
- Pipeline and ColumnTransformer use this feature and define the default style
- Estimators will overwrite some part of the style using the `sk-estimator` class
*/
/* Pipeline and ColumnTransformer style (default) */
#sk-container-id-5 div.sk-toggleable {
/* Default theme specific background. It is overwritten whether we have a
specific estimator or a Pipeline/ColumnTransformer */
background-color: var(--sklearn-color-background);
}
/* Toggleable label */
#sk-container-id-5 label.sk-toggleable__label {
cursor: pointer;
display: flex;
width: 100%;
margin-bottom: 0;
padding: 0.5em;
box-sizing: border-box;
text-align: center;
align-items: start;
justify-content: space-between;
gap: 0.5em;
}
#sk-container-id-5 label.sk-toggleable__label .caption {
font-size: 0.6rem;
font-weight: lighter;
color: var(--sklearn-color-text-muted);
}
#sk-container-id-5 label.sk-toggleable__label-arrow:before {
/* Arrow on the left of the label */
content: "▸";
float: left;
margin-right: 0.25em;
color: var(--sklearn-color-icon);
}
#sk-container-id-5 label.sk-toggleable__label-arrow:hover:before {
color: var(--sklearn-color-text);
}
/* Toggleable content - dropdown */
#sk-container-id-5 div.sk-toggleable__content {
display: none;
text-align: left;
/* unfitted */
background-color: var(--sklearn-color-unfitted-level-0);
}
#sk-container-id-5 div.sk-toggleable__content.fitted {
/* fitted */
background-color: var(--sklearn-color-fitted-level-0);
}
#sk-container-id-5 div.sk-toggleable__content pre {
margin: 0.2em;
border-radius: 0.25em;
color: var(--sklearn-color-text);
/* unfitted */
background-color: var(--sklearn-color-unfitted-level-0);
}
#sk-container-id-5 div.sk-toggleable__content.fitted pre {
/* unfitted */
background-color: var(--sklearn-color-fitted-level-0);
}
#sk-container-id-5 input.sk-toggleable__control:checked~div.sk-toggleable__content {
/* Expand drop-down */
display: block;
width: 100%;
overflow: visible;
}
#sk-container-id-5 input.sk-toggleable__control:checked~label.sk-toggleable__label-arrow:before {
content: "▾";
}
/* Pipeline/ColumnTransformer-specific style */
#sk-container-id-5 div.sk-label input.sk-toggleable__control:checked~label.sk-toggleable__label {
color: var(--sklearn-color-text);
background-color: var(--sklearn-color-unfitted-level-2);
}
#sk-container-id-5 div.sk-label.fitted input.sk-toggleable__control:checked~label.sk-toggleable__label {
background-color: var(--sklearn-color-fitted-level-2);
}
/* Estimator-specific style */
/* Colorize estimator box */
#sk-container-id-5 div.sk-estimator input.sk-toggleable__control:checked~label.sk-toggleable__label {
/* unfitted */
background-color: var(--sklearn-color-unfitted-level-2);
}
#sk-container-id-5 div.sk-estimator.fitted input.sk-toggleable__control:checked~label.sk-toggleable__label {
/* fitted */
background-color: var(--sklearn-color-fitted-level-2);
}
#sk-container-id-5 div.sk-label label.sk-toggleable__label,
#sk-container-id-5 div.sk-label label {
/* The background is the default theme color */
color: var(--sklearn-color-text-on-default-background);
}
/* On hover, darken the color of the background */
#sk-container-id-5 div.sk-label:hover label.sk-toggleable__label {
color: var(--sklearn-color-text);
background-color: var(--sklearn-color-unfitted-level-2);
}
/* Label box, darken color on hover, fitted */
#sk-container-id-5 div.sk-label.fitted:hover label.sk-toggleable__label.fitted {
color: var(--sklearn-color-text);
background-color: var(--sklearn-color-fitted-level-2);
}
/* Estimator label */
#sk-container-id-5 div.sk-label label {
font-family: monospace;
font-weight: bold;
display: inline-block;
line-height: 1.2em;
}
#sk-container-id-5 div.sk-label-container {
text-align: center;
}
/* Estimator-specific */
#sk-container-id-5 div.sk-estimator {
font-family: monospace;
border: 1px dotted var(--sklearn-color-border-box);
border-radius: 0.25em;
box-sizing: border-box;
margin-bottom: 0.5em;
/* unfitted */
background-color: var(--sklearn-color-unfitted-level-0);
}
#sk-container-id-5 div.sk-estimator.fitted {
/* fitted */
background-color: var(--sklearn-color-fitted-level-0);
}
/* on hover */
#sk-container-id-5 div.sk-estimator:hover {
/* unfitted */
background-color: var(--sklearn-color-unfitted-level-2);
}
#sk-container-id-5 div.sk-estimator.fitted:hover {
/* fitted */
background-color: var(--sklearn-color-fitted-level-2);
}
/* Specification for estimator info (e.g. "i" and "?") */
/* Common style for "i" and "?" */
.sk-estimator-doc-link,
a:link.sk-estimator-doc-link,
a:visited.sk-estimator-doc-link {
float: right;
font-size: smaller;
line-height: 1em;
font-family: monospace;
background-color: var(--sklearn-color-background);
border-radius: 1em;
height: 1em;
width: 1em;
text-decoration: none !important;
margin-left: 0.5em;
text-align: center;
/* unfitted */
border: var(--sklearn-color-unfitted-level-1) 1pt solid;
color: var(--sklearn-color-unfitted-level-1);
}
.sk-estimator-doc-link.fitted,
a:link.sk-estimator-doc-link.fitted,
a:visited.sk-estimator-doc-link.fitted {
/* fitted */
border: var(--sklearn-color-fitted-level-1) 1pt solid;
color: var(--sklearn-color-fitted-level-1);
}
/* On hover */
div.sk-estimator:hover .sk-estimator-doc-link:hover,
.sk-estimator-doc-link:hover,
div.sk-label-container:hover .sk-estimator-doc-link:hover,
.sk-estimator-doc-link:hover {
/* unfitted */
background-color: var(--sklearn-color-unfitted-level-3);
color: var(--sklearn-color-background);
text-decoration: none;
}
div.sk-estimator.fitted:hover .sk-estimator-doc-link.fitted:hover,
.sk-estimator-doc-link.fitted:hover,
div.sk-label-container:hover .sk-estimator-doc-link.fitted:hover,
.sk-estimator-doc-link.fitted:hover {
/* fitted */
background-color: var(--sklearn-color-fitted-level-3);
color: var(--sklearn-color-background);
text-decoration: none;
}
/* Span, style for the box shown on hovering the info icon */
.sk-estimator-doc-link span {
display: none;
z-index: 9999;
position: relative;
font-weight: normal;
right: .2ex;
padding: .5ex;
margin: .5ex;
width: min-content;
min-width: 20ex;
max-width: 50ex;
color: var(--sklearn-color-text);
box-shadow: 2pt 2pt 4pt #999;
/* unfitted */
background: var(--sklearn-color-unfitted-level-0);
border: .5pt solid var(--sklearn-color-unfitted-level-3);
}
.sk-estimator-doc-link.fitted span {
/* fitted */
background: var(--sklearn-color-fitted-level-0);
border: var(--sklearn-color-fitted-level-3);
}
.sk-estimator-doc-link:hover span {
display: block;
}
/* "?"-specific style due to the `` HTML tag */
#sk-container-id-5 a.estimator_doc_link {
float: right;
font-size: 1rem;
line-height: 1em;
font-family: monospace;
background-color: var(--sklearn-color-background);
border-radius: 1rem;
height: 1rem;
width: 1rem;
text-decoration: none;
/* unfitted */
color: var(--sklearn-color-unfitted-level-1);
border: var(--sklearn-color-unfitted-level-1) 1pt solid;
}
#sk-container-id-5 a.estimator_doc_link.fitted {
/* fitted */
border: var(--sklearn-color-fitted-level-1) 1pt solid;
color: var(--sklearn-color-fitted-level-1);
}
/* On hover */
#sk-container-id-5 a.estimator_doc_link:hover {
/* unfitted */
background-color: var(--sklearn-color-unfitted-level-3);
color: var(--sklearn-color-background);
text-decoration: none;
}
#sk-container-id-5 a.estimator_doc_link.fitted:hover {
/* fitted */
background-color: var(--sklearn-color-fitted-level-3);
}
.estimator-table summary {
padding: .5rem;
font-family: monospace;
cursor: pointer;
}
.estimator-table details[open] {
padding-left: 0.1rem;
padding-right: 0.1rem;
padding-bottom: 0.3rem;
}
.estimator-table .parameters-table {
margin-left: auto !important;
margin-right: auto !important;
}
.estimator-table .parameters-table tr:nth-child(odd) {
background-color: #fff;
}
.estimator-table .parameters-table tr:nth-child(even) {
background-color: #f6f6f6;
}
.estimator-table .parameters-table tr:hover {
background-color: #e0e0e0;
}
.estimator-table table td {
border: 1px solid rgba(106, 105, 104, 0.232);
}
.user-set td {
color:rgb(255, 94, 0);
text-align: left;
}
.user-set td.value pre {
color:rgb(255, 94, 0) !important;
background-color: transparent !important;
}
.default td {
color: black;
text-align: left;
}
.user-set td i,
.default td i {
color: black;
}
.copy-paste-icon {
background-image: url(data:image/svg+xml;base64,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);
background-repeat: no-repeat;
background-size: 14px 14px;
background-position: 0;
display: inline-block;
width: 14px;
height: 14px;
cursor: pointer;
}
</style>
On GitHub, the HTML representation is unable to render, please try loading this page with nbviewer.org.
<script>function copyToClipboard(text, element) {
// Get the parameter prefix from the closest toggleable content
const toggleableContent = element.closest('.sk-toggleable__content');
const paramPrefix = toggleableContent ? toggleableContent.dataset.paramPrefix : '';
const fullParamName = paramPrefix ? `${paramPrefix}${text}` : text;
const originalStyle = element.style;
const computedStyle = window.getComputedStyle(element);
const originalWidth = computedStyle.width;
const originalHTML = element.innerHTML.replace('Copied!', '');
navigator.clipboard.writeText(fullParamName)
.then(() => {
element.style.width = originalWidth;
element.style.color = 'green';
element.innerHTML = "Copied!";
setTimeout(() => {
element.innerHTML = originalHTML;
element.style = originalStyle;
}, 2000);
})
.catch(err => {
console.error('Failed to copy:', err);
element.style.color = 'red';
element.innerHTML = "Failed!";
setTimeout(() => {
element.innerHTML = originalHTML;
element.style = originalStyle;
}, 2000);
});
return false;
}
document.querySelectorAll('.fa-regular.fa-copy').forEach(function(element) {
const toggleableContent = element.closest('.sk-toggleable__content');
const paramPrefix = toggleableContent ? toggleableContent.dataset.paramPrefix : '';
const paramName = element.parentElement.nextElementSibling.textContent.trim();
const fullParamName = paramPrefix ? `${paramPrefix}${paramName}` : paramName;
element.setAttribute('title', fullParamName);
});
</script>
RandomForestClassifier(n_estimators=5, random_state=42)In a Jupyter environment, please rerun this cell to show the HTML representation or trust the notebook.
On GitHub, the HTML representation is unable to render, please try loading this page with nbviewer.org.
Parameters
| n_estimators | 5 | |
| criterion | 'gini' | |
| max_depth | None | |
| min_samples_split | 2 | |
| min_samples_leaf | 1 | |
| min_weight_fraction_leaf | 0.0 | |
| max_features | 'sqrt' | |
| max_leaf_nodes | None | |
| min_impurity_decrease | 0.0 | |
| bootstrap | True | |
| oob_score | False | |
| n_jobs | None | |
| random_state | 42 | |
| verbose | 0 | |
| warm_start | False | |
| class_weight | None | |
| ccp_alpha | 0.0 | |
| max_samples | None | |
| monotonic_cst | None |
prediction = rf.predict(X_test)print ('Prediction and test: ')
print (prediction)
print (y_test)Prediction and test:
[1 1 0 0 0 1 1 1 0 0 1 0 0 0 0 1 1 0 1 0 0 0 1 0 1 0 0 1 0 0 0 1 1 1 0 0 1
1 0 1 1 0 0 1 1 1 1 1 0 1 0 1 1 0 1 1 0 1 1 1 1 0 1 0 0 1 1 1 0 1 1 1 0 1
0 0 1 0 0 1 0 1 1 1 1 0 1 1 0 0 1 1 0 1 1 1 0 1 1 1 0 0 0 1 0 0 0 1 1 1 1
0 0 0 0 0 0 0 0 0 0 1 0 1 1 1 0 1 0 0 0 1 1 1 1 1 1 1 1 1 0 0 0 0 1 0 0 1
0 1 0 0 0 1 0 1 1 0 1 1 0 1 1 0 0 0 1 0 0 1 1 0 1 1 0 0 1 1 1 1 0 1 0 0 1
0 0 1 1 1 0 1 0 0 1 1 1 1 1 1 1 1 1 1 1 1 1 0 1 1 1 1 0 1 0 1 0 0 0 0 0 0
0 0 1 0 0 0 0 0 0 0 1 0 1 1 0 1 1 0 1 1 1 0 1 0 1 1 0 0]
[1 1 0 0 0 0 1 1 0 0 0 0 0 0 0 1 1 0 1 0 0 0 0 0 1 0 0 1 0 0 0 1 1 0 0 0 1
1 0 1 1 0 0 1 1 1 1 1 0 0 0 1 0 0 1 1 0 1 1 0 1 1 0 0 0 1 1 1 0 1 1 1 0 0
0 0 0 0 1 1 0 1 0 1 1 0 1 1 0 0 1 1 0 1 1 1 0 1 1 1 0 0 0 0 0 0 0 1 0 1 1
0 0 0 1 0 0 0 0 0 0 1 0 1 1 0 1 1 0 0 0 0 1 1 1 1 1 1 1 1 1 0 0 0 1 0 0 1
0 0 0 0 0 0 0 0 0 0 1 1 0 1 1 0 0 0 1 0 0 1 1 0 1 1 0 0 1 1 1 1 0 1 0 0 1
0 0 0 1 1 0 1 0 1 1 1 1 0 1 1 1 1 0 1 1 1 1 1 1 1 0 1 0 1 1 1 0 0 0 0 0 0
0 0 1 1 0 0 0 0 1 0 1 0 1 1 0 1 1 0 1 1 1 0 1 0 1 1 0 1]
print ('Confusion matrix: ')
print (confusion_matrix(y_test, prediction))Confusion matrix:
[[107 23]
[ 11 109]]
print ('Accuracy score: ', accuracy_score(prediction, y_test))Accuracy score: 0.864
print(classification_report(y_test, prediction)) precision recall f1-score support
0 0.91 0.82 0.86 130
1 0.83 0.91 0.87 120
accuracy 0.86 250
macro avg 0.87 0.87 0.86 250
weighted avg 0.87 0.86 0.86 250
roc_auc_score(y_test, prediction)0.8657051282051281plt.xlabel("first feature")
plt.ylabel("second feature")
plot_2d_separator(rf, X, fill=True)
plt.scatter(X[:, 0], X[:, 1], c=y, s=70)<matplotlib.collections.PathCollection at 0x9ff0788>
#RandFor-15rf=RandomForestClassifier(n_estimators=15,random_state=42)rf.fit(X_train, y_train)
<style>#sk-container-id-6 {
/* Definition of color scheme common for light and dark mode */
--sklearn-color-text: #000;
--sklearn-color-text-muted: #666;
--sklearn-color-line: gray;
/* Definition of color scheme for unfitted estimators */
--sklearn-color-unfitted-level-0: #fff5e6;
--sklearn-color-unfitted-level-1: #f6e4d2;
--sklearn-color-unfitted-level-2: #ffe0b3;
--sklearn-color-unfitted-level-3: chocolate;
/* Definition of color scheme for fitted estimators */
--sklearn-color-fitted-level-0: #f0f8ff;
--sklearn-color-fitted-level-1: #d4ebff;
--sklearn-color-fitted-level-2: #b3dbfd;
--sklearn-color-fitted-level-3: cornflowerblue;
/* Specific color for light theme */
--sklearn-color-text-on-default-background: var(--sg-text-color, var(--theme-code-foreground, var(--jp-content-font-color1, black)));
--sklearn-color-background: var(--sg-background-color, var(--theme-background, var(--jp-layout-color0, white)));
--sklearn-color-border-box: var(--sg-text-color, var(--theme-code-foreground, var(--jp-content-font-color1, black)));
--sklearn-color-icon: #696969;
@media (prefers-color-scheme: dark) {
/* Redefinition of color scheme for dark theme */
--sklearn-color-text-on-default-background: var(--sg-text-color, var(--theme-code-foreground, var(--jp-content-font-color1, white)));
--sklearn-color-background: var(--sg-background-color, var(--theme-background, var(--jp-layout-color0, #111)));
--sklearn-color-border-box: var(--sg-text-color, var(--theme-code-foreground, var(--jp-content-font-color1, white)));
--sklearn-color-icon: #878787;
}
}
#sk-container-id-6 {
color: var(--sklearn-color-text);
}
#sk-container-id-6 pre {
padding: 0;
}
#sk-container-id-6 input.sk-hidden--visually {
border: 0;
clip: rect(1px 1px 1px 1px);
clip: rect(1px, 1px, 1px, 1px);
height: 1px;
margin: -1px;
overflow: hidden;
padding: 0;
position: absolute;
width: 1px;
}
#sk-container-id-6 div.sk-dashed-wrapped {
border: 1px dashed var(--sklearn-color-line);
margin: 0 0.4em 0.5em 0.4em;
box-sizing: border-box;
padding-bottom: 0.4em;
background-color: var(--sklearn-color-background);
}
#sk-container-id-6 div.sk-container {
/* jupyter's `normalize.less` sets `[hidden] { display: none; }`
but bootstrap.min.css set `[hidden] { display: none !important; }`
so we also need the `!important` here to be able to override the
default hidden behavior on the sphinx rendered scikit-learn.org.
See: https://github.com/scikit-learn/scikit-learn/issues/21755 */
display: inline-block !important;
position: relative;
}
#sk-container-id-6 div.sk-text-repr-fallback {
display: none;
}
div.sk-parallel-item,
div.sk-serial,
div.sk-item {
/* draw centered vertical line to link estimators */
background-image: linear-gradient(var(--sklearn-color-text-on-default-background), var(--sklearn-color-text-on-default-background));
background-size: 2px 100%;
background-repeat: no-repeat;
background-position: center center;
}
/* Parallel-specific style estimator block */
#sk-container-id-6 div.sk-parallel-item::after {
content: "";
width: 100%;
border-bottom: 2px solid var(--sklearn-color-text-on-default-background);
flex-grow: 1;
}
#sk-container-id-6 div.sk-parallel {
display: flex;
align-items: stretch;
justify-content: center;
background-color: var(--sklearn-color-background);
position: relative;
}
#sk-container-id-6 div.sk-parallel-item {
display: flex;
flex-direction: column;
}
#sk-container-id-6 div.sk-parallel-item:first-child::after {
align-self: flex-end;
width: 50%;
}
#sk-container-id-6 div.sk-parallel-item:last-child::after {
align-self: flex-start;
width: 50%;
}
#sk-container-id-6 div.sk-parallel-item:only-child::after {
width: 0;
}
/* Serial-specific style estimator block */
#sk-container-id-6 div.sk-serial {
display: flex;
flex-direction: column;
align-items: center;
background-color: var(--sklearn-color-background);
padding-right: 1em;
padding-left: 1em;
}
/* Toggleable style: style used for estimator/Pipeline/ColumnTransformer box that is
clickable and can be expanded/collapsed.
- Pipeline and ColumnTransformer use this feature and define the default style
- Estimators will overwrite some part of the style using the `sk-estimator` class
*/
/* Pipeline and ColumnTransformer style (default) */
#sk-container-id-6 div.sk-toggleable {
/* Default theme specific background. It is overwritten whether we have a
specific estimator or a Pipeline/ColumnTransformer */
background-color: var(--sklearn-color-background);
}
/* Toggleable label */
#sk-container-id-6 label.sk-toggleable__label {
cursor: pointer;
display: flex;
width: 100%;
margin-bottom: 0;
padding: 0.5em;
box-sizing: border-box;
text-align: center;
align-items: start;
justify-content: space-between;
gap: 0.5em;
}
#sk-container-id-6 label.sk-toggleable__label .caption {
font-size: 0.6rem;
font-weight: lighter;
color: var(--sklearn-color-text-muted);
}
#sk-container-id-6 label.sk-toggleable__label-arrow:before {
/* Arrow on the left of the label */
content: "▸";
float: left;
margin-right: 0.25em;
color: var(--sklearn-color-icon);
}
#sk-container-id-6 label.sk-toggleable__label-arrow:hover:before {
color: var(--sklearn-color-text);
}
/* Toggleable content - dropdown */
#sk-container-id-6 div.sk-toggleable__content {
display: none;
text-align: left;
/* unfitted */
background-color: var(--sklearn-color-unfitted-level-0);
}
#sk-container-id-6 div.sk-toggleable__content.fitted {
/* fitted */
background-color: var(--sklearn-color-fitted-level-0);
}
#sk-container-id-6 div.sk-toggleable__content pre {
margin: 0.2em;
border-radius: 0.25em;
color: var(--sklearn-color-text);
/* unfitted */
background-color: var(--sklearn-color-unfitted-level-0);
}
#sk-container-id-6 div.sk-toggleable__content.fitted pre {
/* unfitted */
background-color: var(--sklearn-color-fitted-level-0);
}
#sk-container-id-6 input.sk-toggleable__control:checked~div.sk-toggleable__content {
/* Expand drop-down */
display: block;
width: 100%;
overflow: visible;
}
#sk-container-id-6 input.sk-toggleable__control:checked~label.sk-toggleable__label-arrow:before {
content: "▾";
}
/* Pipeline/ColumnTransformer-specific style */
#sk-container-id-6 div.sk-label input.sk-toggleable__control:checked~label.sk-toggleable__label {
color: var(--sklearn-color-text);
background-color: var(--sklearn-color-unfitted-level-2);
}
#sk-container-id-6 div.sk-label.fitted input.sk-toggleable__control:checked~label.sk-toggleable__label {
background-color: var(--sklearn-color-fitted-level-2);
}
/* Estimator-specific style */
/* Colorize estimator box */
#sk-container-id-6 div.sk-estimator input.sk-toggleable__control:checked~label.sk-toggleable__label {
/* unfitted */
background-color: var(--sklearn-color-unfitted-level-2);
}
#sk-container-id-6 div.sk-estimator.fitted input.sk-toggleable__control:checked~label.sk-toggleable__label {
/* fitted */
background-color: var(--sklearn-color-fitted-level-2);
}
#sk-container-id-6 div.sk-label label.sk-toggleable__label,
#sk-container-id-6 div.sk-label label {
/* The background is the default theme color */
color: var(--sklearn-color-text-on-default-background);
}
/* On hover, darken the color of the background */
#sk-container-id-6 div.sk-label:hover label.sk-toggleable__label {
color: var(--sklearn-color-text);
background-color: var(--sklearn-color-unfitted-level-2);
}
/* Label box, darken color on hover, fitted */
#sk-container-id-6 div.sk-label.fitted:hover label.sk-toggleable__label.fitted {
color: var(--sklearn-color-text);
background-color: var(--sklearn-color-fitted-level-2);
}
/* Estimator label */
#sk-container-id-6 div.sk-label label {
font-family: monospace;
font-weight: bold;
display: inline-block;
line-height: 1.2em;
}
#sk-container-id-6 div.sk-label-container {
text-align: center;
}
/* Estimator-specific */
#sk-container-id-6 div.sk-estimator {
font-family: monospace;
border: 1px dotted var(--sklearn-color-border-box);
border-radius: 0.25em;
box-sizing: border-box;
margin-bottom: 0.5em;
/* unfitted */
background-color: var(--sklearn-color-unfitted-level-0);
}
#sk-container-id-6 div.sk-estimator.fitted {
/* fitted */
background-color: var(--sklearn-color-fitted-level-0);
}
/* on hover */
#sk-container-id-6 div.sk-estimator:hover {
/* unfitted */
background-color: var(--sklearn-color-unfitted-level-2);
}
#sk-container-id-6 div.sk-estimator.fitted:hover {
/* fitted */
background-color: var(--sklearn-color-fitted-level-2);
}
/* Specification for estimator info (e.g. "i" and "?") */
/* Common style for "i" and "?" */
.sk-estimator-doc-link,
a:link.sk-estimator-doc-link,
a:visited.sk-estimator-doc-link {
float: right;
font-size: smaller;
line-height: 1em;
font-family: monospace;
background-color: var(--sklearn-color-background);
border-radius: 1em;
height: 1em;
width: 1em;
text-decoration: none !important;
margin-left: 0.5em;
text-align: center;
/* unfitted */
border: var(--sklearn-color-unfitted-level-1) 1pt solid;
color: var(--sklearn-color-unfitted-level-1);
}
.sk-estimator-doc-link.fitted,
a:link.sk-estimator-doc-link.fitted,
a:visited.sk-estimator-doc-link.fitted {
/* fitted */
border: var(--sklearn-color-fitted-level-1) 1pt solid;
color: var(--sklearn-color-fitted-level-1);
}
/* On hover */
div.sk-estimator:hover .sk-estimator-doc-link:hover,
.sk-estimator-doc-link:hover,
div.sk-label-container:hover .sk-estimator-doc-link:hover,
.sk-estimator-doc-link:hover {
/* unfitted */
background-color: var(--sklearn-color-unfitted-level-3);
color: var(--sklearn-color-background);
text-decoration: none;
}
div.sk-estimator.fitted:hover .sk-estimator-doc-link.fitted:hover,
.sk-estimator-doc-link.fitted:hover,
div.sk-label-container:hover .sk-estimator-doc-link.fitted:hover,
.sk-estimator-doc-link.fitted:hover {
/* fitted */
background-color: var(--sklearn-color-fitted-level-3);
color: var(--sklearn-color-background);
text-decoration: none;
}
/* Span, style for the box shown on hovering the info icon */
.sk-estimator-doc-link span {
display: none;
z-index: 9999;
position: relative;
font-weight: normal;
right: .2ex;
padding: .5ex;
margin: .5ex;
width: min-content;
min-width: 20ex;
max-width: 50ex;
color: var(--sklearn-color-text);
box-shadow: 2pt 2pt 4pt #999;
/* unfitted */
background: var(--sklearn-color-unfitted-level-0);
border: .5pt solid var(--sklearn-color-unfitted-level-3);
}
.sk-estimator-doc-link.fitted span {
/* fitted */
background: var(--sklearn-color-fitted-level-0);
border: var(--sklearn-color-fitted-level-3);
}
.sk-estimator-doc-link:hover span {
display: block;
}
/* "?"-specific style due to the `` HTML tag */
#sk-container-id-6 a.estimator_doc_link {
float: right;
font-size: 1rem;
line-height: 1em;
font-family: monospace;
background-color: var(--sklearn-color-background);
border-radius: 1rem;
height: 1rem;
width: 1rem;
text-decoration: none;
/* unfitted */
color: var(--sklearn-color-unfitted-level-1);
border: var(--sklearn-color-unfitted-level-1) 1pt solid;
}
#sk-container-id-6 a.estimator_doc_link.fitted {
/* fitted */
border: var(--sklearn-color-fitted-level-1) 1pt solid;
color: var(--sklearn-color-fitted-level-1);
}
/* On hover */
#sk-container-id-6 a.estimator_doc_link:hover {
/* unfitted */
background-color: var(--sklearn-color-unfitted-level-3);
color: var(--sklearn-color-background);
text-decoration: none;
}
#sk-container-id-6 a.estimator_doc_link.fitted:hover {
/* fitted */
background-color: var(--sklearn-color-fitted-level-3);
}
.estimator-table summary {
padding: .5rem;
font-family: monospace;
cursor: pointer;
}
.estimator-table details[open] {
padding-left: 0.1rem;
padding-right: 0.1rem;
padding-bottom: 0.3rem;
}
.estimator-table .parameters-table {
margin-left: auto !important;
margin-right: auto !important;
}
.estimator-table .parameters-table tr:nth-child(odd) {
background-color: #fff;
}
.estimator-table .parameters-table tr:nth-child(even) {
background-color: #f6f6f6;
}
.estimator-table .parameters-table tr:hover {
background-color: #e0e0e0;
}
.estimator-table table td {
border: 1px solid rgba(106, 105, 104, 0.232);
}
.user-set td {
color:rgb(255, 94, 0);
text-align: left;
}
.user-set td.value pre {
color:rgb(255, 94, 0) !important;
background-color: transparent !important;
}
.default td {
color: black;
text-align: left;
}
.user-set td i,
.default td i {
color: black;
}
.copy-paste-icon {
background-image: url(data:image/svg+xml;base64,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);
background-repeat: no-repeat;
background-size: 14px 14px;
background-position: 0;
display: inline-block;
width: 14px;
height: 14px;
cursor: pointer;
}
</style>
On GitHub, the HTML representation is unable to render, please try loading this page with nbviewer.org.
<script>function copyToClipboard(text, element) {
// Get the parameter prefix from the closest toggleable content
const toggleableContent = element.closest('.sk-toggleable__content');
const paramPrefix = toggleableContent ? toggleableContent.dataset.paramPrefix : '';
const fullParamName = paramPrefix ? `${paramPrefix}${text}` : text;
const originalStyle = element.style;
const computedStyle = window.getComputedStyle(element);
const originalWidth = computedStyle.width;
const originalHTML = element.innerHTML.replace('Copied!', '');
navigator.clipboard.writeText(fullParamName)
.then(() => {
element.style.width = originalWidth;
element.style.color = 'green';
element.innerHTML = "Copied!";
setTimeout(() => {
element.innerHTML = originalHTML;
element.style = originalStyle;
}, 2000);
})
.catch(err => {
console.error('Failed to copy:', err);
element.style.color = 'red';
element.innerHTML = "Failed!";
setTimeout(() => {
element.innerHTML = originalHTML;
element.style = originalStyle;
}, 2000);
});
return false;
}
document.querySelectorAll('.fa-regular.fa-copy').forEach(function(element) {
const toggleableContent = element.closest('.sk-toggleable__content');
const paramPrefix = toggleableContent ? toggleableContent.dataset.paramPrefix : '';
const paramName = element.parentElement.nextElementSibling.textContent.trim();
const fullParamName = paramPrefix ? `${paramPrefix}${paramName}` : paramName;
element.setAttribute('title', fullParamName);
});
</script>
RandomForestClassifier(n_estimators=15, random_state=42)In a Jupyter environment, please rerun this cell to show the HTML representation or trust the notebook.
On GitHub, the HTML representation is unable to render, please try loading this page with nbviewer.org.
Parameters
| n_estimators | 15 | |
| criterion | 'gini' | |
| max_depth | None | |
| min_samples_split | 2 | |
| min_samples_leaf | 1 | |
| min_weight_fraction_leaf | 0.0 | |
| max_features | 'sqrt' | |
| max_leaf_nodes | None | |
| min_impurity_decrease | 0.0 | |
| bootstrap | True | |
| oob_score | False | |
| n_jobs | None | |
| random_state | 42 | |
| verbose | 0 | |
| warm_start | False | |
| class_weight | None | |
| ccp_alpha | 0.0 | |
| max_samples | None | |
| monotonic_cst | None |
prediction = rf.predict(X_test)print ('Prediction and test: ')
print (prediction)
print (y_test)Prediction and test:
[1 1 0 0 0 1 1 1 0 0 1 0 0 0 0 1 1 0 1 0 0 0 1 0 1 0 0 1 0 0 0 1 1 1 0 0 1
1 0 1 1 0 0 1 1 1 1 1 0 1 0 1 1 0 1 1 0 1 1 0 1 0 1 0 0 1 1 1 0 1 0 1 0 1
0 0 1 0 1 1 0 1 1 1 1 0 1 1 0 0 1 1 0 1 1 1 0 1 1 1 0 0 0 1 0 0 0 1 1 1 1
0 0 0 0 0 0 0 0 0 0 1 0 1 1 1 0 1 0 0 0 1 1 1 1 1 1 1 1 0 1 0 0 0 1 0 0 1
0 1 0 0 0 0 0 1 1 0 1 1 0 1 1 0 0 0 1 0 0 1 1 0 1 1 0 0 1 1 1 1 0 1 0 0 1
0 0 1 1 1 0 1 0 0 1 1 1 1 1 1 1 1 1 1 1 1 1 0 1 1 1 1 0 1 0 1 0 0 0 0 0 0
0 0 1 1 0 0 0 0 1 0 1 0 1 1 0 1 1 0 1 1 1 0 1 0 1 1 0 1]
[1 1 0 0 0 0 1 1 0 0 0 0 0 0 0 1 1 0 1 0 0 0 0 0 1 0 0 1 0 0 0 1 1 0 0 0 1
1 0 1 1 0 0 1 1 1 1 1 0 0 0 1 0 0 1 1 0 1 1 0 1 1 0 0 0 1 1 1 0 1 1 1 0 0
0 0 0 0 1 1 0 1 0 1 1 0 1 1 0 0 1 1 0 1 1 1 0 1 1 1 0 0 0 0 0 0 0 1 0 1 1
0 0 0 1 0 0 0 0 0 0 1 0 1 1 0 1 1 0 0 0 0 1 1 1 1 1 1 1 1 1 0 0 0 1 0 0 1
0 0 0 0 0 0 0 0 0 0 1 1 0 1 1 0 0 0 1 0 0 1 1 0 1 1 0 0 1 1 1 1 0 1 0 0 1
0 0 0 1 1 0 1 0 1 1 1 1 0 1 1 1 1 0 1 1 1 1 1 1 1 0 1 0 1 1 1 0 0 0 0 0 0
0 0 1 1 0 0 0 0 1 0 1 0 1 1 0 1 1 0 1 1 1 0 1 0 1 1 0 1]
print ('Confusion matrix: ')
print (confusion_matrix(y_test, prediction))Confusion matrix:
[[109 21]
[ 8 112]]
print ('Accuracy score: ', accuracy_score(prediction, y_test))Accuracy score: 0.884
print(classification_report(y_test, prediction)) precision recall f1-score support
0 0.93 0.84 0.88 130
1 0.84 0.93 0.89 120
accuracy 0.88 250
macro avg 0.89 0.89 0.88 250
weighted avg 0.89 0.88 0.88 250
roc_auc_score(y_test, prediction)0.885897435897436plt.xlabel("first feature")
plt.ylabel("second feature")
plot_2d_separator(rf, X, fill=True)
plt.scatter(X[:, 0], X[:, 1], c=y, s=70)<matplotlib.collections.PathCollection at 0xa303e60>
#RandFor-50rf=RandomForestClassifier(n_estimators=50,random_state=42)rf.fit(X_train, y_train)
<style>#sk-container-id-7 {
/* Definition of color scheme common for light and dark mode */
--sklearn-color-text: #000;
--sklearn-color-text-muted: #666;
--sklearn-color-line: gray;
/* Definition of color scheme for unfitted estimators */
--sklearn-color-unfitted-level-0: #fff5e6;
--sklearn-color-unfitted-level-1: #f6e4d2;
--sklearn-color-unfitted-level-2: #ffe0b3;
--sklearn-color-unfitted-level-3: chocolate;
/* Definition of color scheme for fitted estimators */
--sklearn-color-fitted-level-0: #f0f8ff;
--sklearn-color-fitted-level-1: #d4ebff;
--sklearn-color-fitted-level-2: #b3dbfd;
--sklearn-color-fitted-level-3: cornflowerblue;
/* Specific color for light theme */
--sklearn-color-text-on-default-background: var(--sg-text-color, var(--theme-code-foreground, var(--jp-content-font-color1, black)));
--sklearn-color-background: var(--sg-background-color, var(--theme-background, var(--jp-layout-color0, white)));
--sklearn-color-border-box: var(--sg-text-color, var(--theme-code-foreground, var(--jp-content-font-color1, black)));
--sklearn-color-icon: #696969;
@media (prefers-color-scheme: dark) {
/* Redefinition of color scheme for dark theme */
--sklearn-color-text-on-default-background: var(--sg-text-color, var(--theme-code-foreground, var(--jp-content-font-color1, white)));
--sklearn-color-background: var(--sg-background-color, var(--theme-background, var(--jp-layout-color0, #111)));
--sklearn-color-border-box: var(--sg-text-color, var(--theme-code-foreground, var(--jp-content-font-color1, white)));
--sklearn-color-icon: #878787;
}
}
#sk-container-id-7 {
color: var(--sklearn-color-text);
}
#sk-container-id-7 pre {
padding: 0;
}
#sk-container-id-7 input.sk-hidden--visually {
border: 0;
clip: rect(1px 1px 1px 1px);
clip: rect(1px, 1px, 1px, 1px);
height: 1px;
margin: -1px;
overflow: hidden;
padding: 0;
position: absolute;
width: 1px;
}
#sk-container-id-7 div.sk-dashed-wrapped {
border: 1px dashed var(--sklearn-color-line);
margin: 0 0.4em 0.5em 0.4em;
box-sizing: border-box;
padding-bottom: 0.4em;
background-color: var(--sklearn-color-background);
}
#sk-container-id-7 div.sk-container {
/* jupyter's `normalize.less` sets `[hidden] { display: none; }`
but bootstrap.min.css set `[hidden] { display: none !important; }`
so we also need the `!important` here to be able to override the
default hidden behavior on the sphinx rendered scikit-learn.org.
See: https://github.com/scikit-learn/scikit-learn/issues/21755 */
display: inline-block !important;
position: relative;
}
#sk-container-id-7 div.sk-text-repr-fallback {
display: none;
}
div.sk-parallel-item,
div.sk-serial,
div.sk-item {
/* draw centered vertical line to link estimators */
background-image: linear-gradient(var(--sklearn-color-text-on-default-background), var(--sklearn-color-text-on-default-background));
background-size: 2px 100%;
background-repeat: no-repeat;
background-position: center center;
}
/* Parallel-specific style estimator block */
#sk-container-id-7 div.sk-parallel-item::after {
content: "";
width: 100%;
border-bottom: 2px solid var(--sklearn-color-text-on-default-background);
flex-grow: 1;
}
#sk-container-id-7 div.sk-parallel {
display: flex;
align-items: stretch;
justify-content: center;
background-color: var(--sklearn-color-background);
position: relative;
}
#sk-container-id-7 div.sk-parallel-item {
display: flex;
flex-direction: column;
}
#sk-container-id-7 div.sk-parallel-item:first-child::after {
align-self: flex-end;
width: 50%;
}
#sk-container-id-7 div.sk-parallel-item:last-child::after {
align-self: flex-start;
width: 50%;
}
#sk-container-id-7 div.sk-parallel-item:only-child::after {
width: 0;
}
/* Serial-specific style estimator block */
#sk-container-id-7 div.sk-serial {
display: flex;
flex-direction: column;
align-items: center;
background-color: var(--sklearn-color-background);
padding-right: 1em;
padding-left: 1em;
}
/* Toggleable style: style used for estimator/Pipeline/ColumnTransformer box that is
clickable and can be expanded/collapsed.
- Pipeline and ColumnTransformer use this feature and define the default style
- Estimators will overwrite some part of the style using the `sk-estimator` class
*/
/* Pipeline and ColumnTransformer style (default) */
#sk-container-id-7 div.sk-toggleable {
/* Default theme specific background. It is overwritten whether we have a
specific estimator or a Pipeline/ColumnTransformer */
background-color: var(--sklearn-color-background);
}
/* Toggleable label */
#sk-container-id-7 label.sk-toggleable__label {
cursor: pointer;
display: flex;
width: 100%;
margin-bottom: 0;
padding: 0.5em;
box-sizing: border-box;
text-align: center;
align-items: start;
justify-content: space-between;
gap: 0.5em;
}
#sk-container-id-7 label.sk-toggleable__label .caption {
font-size: 0.6rem;
font-weight: lighter;
color: var(--sklearn-color-text-muted);
}
#sk-container-id-7 label.sk-toggleable__label-arrow:before {
/* Arrow on the left of the label */
content: "▸";
float: left;
margin-right: 0.25em;
color: var(--sklearn-color-icon);
}
#sk-container-id-7 label.sk-toggleable__label-arrow:hover:before {
color: var(--sklearn-color-text);
}
/* Toggleable content - dropdown */
#sk-container-id-7 div.sk-toggleable__content {
display: none;
text-align: left;
/* unfitted */
background-color: var(--sklearn-color-unfitted-level-0);
}
#sk-container-id-7 div.sk-toggleable__content.fitted {
/* fitted */
background-color: var(--sklearn-color-fitted-level-0);
}
#sk-container-id-7 div.sk-toggleable__content pre {
margin: 0.2em;
border-radius: 0.25em;
color: var(--sklearn-color-text);
/* unfitted */
background-color: var(--sklearn-color-unfitted-level-0);
}
#sk-container-id-7 div.sk-toggleable__content.fitted pre {
/* unfitted */
background-color: var(--sklearn-color-fitted-level-0);
}
#sk-container-id-7 input.sk-toggleable__control:checked~div.sk-toggleable__content {
/* Expand drop-down */
display: block;
width: 100%;
overflow: visible;
}
#sk-container-id-7 input.sk-toggleable__control:checked~label.sk-toggleable__label-arrow:before {
content: "▾";
}
/* Pipeline/ColumnTransformer-specific style */
#sk-container-id-7 div.sk-label input.sk-toggleable__control:checked~label.sk-toggleable__label {
color: var(--sklearn-color-text);
background-color: var(--sklearn-color-unfitted-level-2);
}
#sk-container-id-7 div.sk-label.fitted input.sk-toggleable__control:checked~label.sk-toggleable__label {
background-color: var(--sklearn-color-fitted-level-2);
}
/* Estimator-specific style */
/* Colorize estimator box */
#sk-container-id-7 div.sk-estimator input.sk-toggleable__control:checked~label.sk-toggleable__label {
/* unfitted */
background-color: var(--sklearn-color-unfitted-level-2);
}
#sk-container-id-7 div.sk-estimator.fitted input.sk-toggleable__control:checked~label.sk-toggleable__label {
/* fitted */
background-color: var(--sklearn-color-fitted-level-2);
}
#sk-container-id-7 div.sk-label label.sk-toggleable__label,
#sk-container-id-7 div.sk-label label {
/* The background is the default theme color */
color: var(--sklearn-color-text-on-default-background);
}
/* On hover, darken the color of the background */
#sk-container-id-7 div.sk-label:hover label.sk-toggleable__label {
color: var(--sklearn-color-text);
background-color: var(--sklearn-color-unfitted-level-2);
}
/* Label box, darken color on hover, fitted */
#sk-container-id-7 div.sk-label.fitted:hover label.sk-toggleable__label.fitted {
color: var(--sklearn-color-text);
background-color: var(--sklearn-color-fitted-level-2);
}
/* Estimator label */
#sk-container-id-7 div.sk-label label {
font-family: monospace;
font-weight: bold;
display: inline-block;
line-height: 1.2em;
}
#sk-container-id-7 div.sk-label-container {
text-align: center;
}
/* Estimator-specific */
#sk-container-id-7 div.sk-estimator {
font-family: monospace;
border: 1px dotted var(--sklearn-color-border-box);
border-radius: 0.25em;
box-sizing: border-box;
margin-bottom: 0.5em;
/* unfitted */
background-color: var(--sklearn-color-unfitted-level-0);
}
#sk-container-id-7 div.sk-estimator.fitted {
/* fitted */
background-color: var(--sklearn-color-fitted-level-0);
}
/* on hover */
#sk-container-id-7 div.sk-estimator:hover {
/* unfitted */
background-color: var(--sklearn-color-unfitted-level-2);
}
#sk-container-id-7 div.sk-estimator.fitted:hover {
/* fitted */
background-color: var(--sklearn-color-fitted-level-2);
}
/* Specification for estimator info (e.g. "i" and "?") */
/* Common style for "i" and "?" */
.sk-estimator-doc-link,
a:link.sk-estimator-doc-link,
a:visited.sk-estimator-doc-link {
float: right;
font-size: smaller;
line-height: 1em;
font-family: monospace;
background-color: var(--sklearn-color-background);
border-radius: 1em;
height: 1em;
width: 1em;
text-decoration: none !important;
margin-left: 0.5em;
text-align: center;
/* unfitted */
border: var(--sklearn-color-unfitted-level-1) 1pt solid;
color: var(--sklearn-color-unfitted-level-1);
}
.sk-estimator-doc-link.fitted,
a:link.sk-estimator-doc-link.fitted,
a:visited.sk-estimator-doc-link.fitted {
/* fitted */
border: var(--sklearn-color-fitted-level-1) 1pt solid;
color: var(--sklearn-color-fitted-level-1);
}
/* On hover */
div.sk-estimator:hover .sk-estimator-doc-link:hover,
.sk-estimator-doc-link:hover,
div.sk-label-container:hover .sk-estimator-doc-link:hover,
.sk-estimator-doc-link:hover {
/* unfitted */
background-color: var(--sklearn-color-unfitted-level-3);
color: var(--sklearn-color-background);
text-decoration: none;
}
div.sk-estimator.fitted:hover .sk-estimator-doc-link.fitted:hover,
.sk-estimator-doc-link.fitted:hover,
div.sk-label-container:hover .sk-estimator-doc-link.fitted:hover,
.sk-estimator-doc-link.fitted:hover {
/* fitted */
background-color: var(--sklearn-color-fitted-level-3);
color: var(--sklearn-color-background);
text-decoration: none;
}
/* Span, style for the box shown on hovering the info icon */
.sk-estimator-doc-link span {
display: none;
z-index: 9999;
position: relative;
font-weight: normal;
right: .2ex;
padding: .5ex;
margin: .5ex;
width: min-content;
min-width: 20ex;
max-width: 50ex;
color: var(--sklearn-color-text);
box-shadow: 2pt 2pt 4pt #999;
/* unfitted */
background: var(--sklearn-color-unfitted-level-0);
border: .5pt solid var(--sklearn-color-unfitted-level-3);
}
.sk-estimator-doc-link.fitted span {
/* fitted */
background: var(--sklearn-color-fitted-level-0);
border: var(--sklearn-color-fitted-level-3);
}
.sk-estimator-doc-link:hover span {
display: block;
}
/* "?"-specific style due to the `` HTML tag */
#sk-container-id-7 a.estimator_doc_link {
float: right;
font-size: 1rem;
line-height: 1em;
font-family: monospace;
background-color: var(--sklearn-color-background);
border-radius: 1rem;
height: 1rem;
width: 1rem;
text-decoration: none;
/* unfitted */
color: var(--sklearn-color-unfitted-level-1);
border: var(--sklearn-color-unfitted-level-1) 1pt solid;
}
#sk-container-id-7 a.estimator_doc_link.fitted {
/* fitted */
border: var(--sklearn-color-fitted-level-1) 1pt solid;
color: var(--sklearn-color-fitted-level-1);
}
/* On hover */
#sk-container-id-7 a.estimator_doc_link:hover {
/* unfitted */
background-color: var(--sklearn-color-unfitted-level-3);
color: var(--sklearn-color-background);
text-decoration: none;
}
#sk-container-id-7 a.estimator_doc_link.fitted:hover {
/* fitted */
background-color: var(--sklearn-color-fitted-level-3);
}
.estimator-table summary {
padding: .5rem;
font-family: monospace;
cursor: pointer;
}
.estimator-table details[open] {
padding-left: 0.1rem;
padding-right: 0.1rem;
padding-bottom: 0.3rem;
}
.estimator-table .parameters-table {
margin-left: auto !important;
margin-right: auto !important;
}
.estimator-table .parameters-table tr:nth-child(odd) {
background-color: #fff;
}
.estimator-table .parameters-table tr:nth-child(even) {
background-color: #f6f6f6;
}
.estimator-table .parameters-table tr:hover {
background-color: #e0e0e0;
}
.estimator-table table td {
border: 1px solid rgba(106, 105, 104, 0.232);
}
.user-set td {
color:rgb(255, 94, 0);
text-align: left;
}
.user-set td.value pre {
color:rgb(255, 94, 0) !important;
background-color: transparent !important;
}
.default td {
color: black;
text-align: left;
}
.user-set td i,
.default td i {
color: black;
}
.copy-paste-icon {
background-image: url(data:image/svg+xml;base64,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);
background-repeat: no-repeat;
background-size: 14px 14px;
background-position: 0;
display: inline-block;
width: 14px;
height: 14px;
cursor: pointer;
}
</style>
On GitHub, the HTML representation is unable to render, please try loading this page with nbviewer.org.
<script>function copyToClipboard(text, element) {
// Get the parameter prefix from the closest toggleable content
const toggleableContent = element.closest('.sk-toggleable__content');
const paramPrefix = toggleableContent ? toggleableContent.dataset.paramPrefix : '';
const fullParamName = paramPrefix ? `${paramPrefix}${text}` : text;
const originalStyle = element.style;
const computedStyle = window.getComputedStyle(element);
const originalWidth = computedStyle.width;
const originalHTML = element.innerHTML.replace('Copied!', '');
navigator.clipboard.writeText(fullParamName)
.then(() => {
element.style.width = originalWidth;
element.style.color = 'green';
element.innerHTML = "Copied!";
setTimeout(() => {
element.innerHTML = originalHTML;
element.style = originalStyle;
}, 2000);
})
.catch(err => {
console.error('Failed to copy:', err);
element.style.color = 'red';
element.innerHTML = "Failed!";
setTimeout(() => {
element.innerHTML = originalHTML;
element.style = originalStyle;
}, 2000);
});
return false;
}
document.querySelectorAll('.fa-regular.fa-copy').forEach(function(element) {
const toggleableContent = element.closest('.sk-toggleable__content');
const paramPrefix = toggleableContent ? toggleableContent.dataset.paramPrefix : '';
const paramName = element.parentElement.nextElementSibling.textContent.trim();
const fullParamName = paramPrefix ? `${paramPrefix}${paramName}` : paramName;
element.setAttribute('title', fullParamName);
});
</script>
RandomForestClassifier(n_estimators=50, random_state=42)In a Jupyter environment, please rerun this cell to show the HTML representation or trust the notebook.
On GitHub, the HTML representation is unable to render, please try loading this page with nbviewer.org.
Parameters
| n_estimators | 50 | |
| criterion | 'gini' | |
| max_depth | None | |
| min_samples_split | 2 | |
| min_samples_leaf | 1 | |
| min_weight_fraction_leaf | 0.0 | |
| max_features | 'sqrt' | |
| max_leaf_nodes | None | |
| min_impurity_decrease | 0.0 | |
| bootstrap | True | |
| oob_score | False | |
| n_jobs | None | |
| random_state | 42 | |
| verbose | 0 | |
| warm_start | False | |
| class_weight | None | |
| ccp_alpha | 0.0 | |
| max_samples | None | |
| monotonic_cst | None |
prediction = rf.predict(X_test)print ('Prediction and test: ')
print (prediction)
print (y_test)Prediction and test:
[1 1 0 0 0 1 1 1 0 0 1 0 0 0 0 1 1 0 1 0 0 0 1 0 1 0 0 1 0 0 0 1 1 0 0 0 1
1 0 1 1 0 0 1 1 1 1 1 0 1 0 1 1 0 0 1 0 1 1 0 1 1 1 0 0 1 1 1 0 1 0 1 0 1
0 0 1 0 1 1 0 1 1 1 1 0 1 1 0 0 1 1 0 1 1 1 0 1 1 1 0 0 0 1 0 0 0 1 1 1 1
0 0 0 0 0 0 0 0 0 0 1 0 1 1 1 0 1 0 0 0 1 1 1 1 1 1 1 1 0 1 0 0 0 0 0 0 1
0 1 0 0 0 0 0 1 1 0 1 1 0 1 1 0 0 0 1 0 0 1 1 0 1 1 0 0 1 1 1 1 0 1 0 0 1
0 0 1 1 1 0 1 0 0 1 1 1 1 1 1 1 1 1 1 1 1 1 0 1 1 1 1 0 1 0 1 0 0 0 0 0 0
0 0 1 1 0 0 0 0 1 0 1 0 1 1 0 1 1 0 1 1 1 0 1 0 1 1 0 1]
[1 1 0 0 0 0 1 1 0 0 0 0 0 0 0 1 1 0 1 0 0 0 0 0 1 0 0 1 0 0 0 1 1 0 0 0 1
1 0 1 1 0 0 1 1 1 1 1 0 0 0 1 0 0 1 1 0 1 1 0 1 1 0 0 0 1 1 1 0 1 1 1 0 0
0 0 0 0 1 1 0 1 0 1 1 0 1 1 0 0 1 1 0 1 1 1 0 1 1 1 0 0 0 0 0 0 0 1 0 1 1
0 0 0 1 0 0 0 0 0 0 1 0 1 1 0 1 1 0 0 0 0 1 1 1 1 1 1 1 1 1 0 0 0 1 0 0 1
0 0 0 0 0 0 0 0 0 0 1 1 0 1 1 0 0 0 1 0 0 1 1 0 1 1 0 0 1 1 1 1 0 1 0 0 1
0 0 0 1 1 0 1 0 1 1 1 1 0 1 1 1 1 0 1 1 1 1 1 1 1 0 1 0 1 1 1 0 0 0 0 0 0
0 0 1 1 0 0 0 0 1 0 1 0 1 1 0 1 1 0 1 1 1 0 1 0 1 1 0 1]
print ('Confusion matrix: ')
print (confusion_matrix(y_test, prediction))Confusion matrix:
[[110 20]
[ 9 111]]
print ('Accuracy score: ', accuracy_score(prediction, y_test))Accuracy score: 0.884
print(classification_report(y_test, prediction)) precision recall f1-score support
0 0.92 0.85 0.88 130
1 0.85 0.93 0.88 120
accuracy 0.88 250
macro avg 0.89 0.89 0.88 250
weighted avg 0.89 0.88 0.88 250
roc_auc_score(y_test, prediction)0.885576923076923plt.xlabel("first feature")
plt.ylabel("second feature")
plot_2d_separator(rf, X, fill=True)
plt.scatter(X[:, 0], X[:, 1], c=y, s=70)<matplotlib.collections.PathCollection at 0xa4bb060>