From 778ca9a42dd94449814ef7e8ed641c2ff3736e75 Mon Sep 17 00:00:00 2001 From: MachulinaDV Date: Wed, 11 Mar 2026 15:41:50 +0000 Subject: [PATCH] =?UTF-8?q?=D0=97=D0=B0=D0=B3=D1=80=D1=83=D0=B7=D0=B8?= =?UTF-8?q?=D1=82=D1=8C=20=D1=84=D0=B0=D0=B9=D0=BB=D1=8B=20=D0=B2=20=C2=AB?= =?UTF-8?q?lab1=C2=BB?= MIME-Version: 1.0 Content-Type: text/plain; charset=UTF-8 Content-Transfer-Encoding: 8bit --- lab1/Lab01_Report.md | 2150 +++++++++++++++++++++++++++++++++++++++ lab1/Untitled (1).ipynb | 1296 +++++++++++++++++++++++ lab1/lab1.xlsx | Bin 0 -> 12216 bytes lab1/train(2).png | Bin 0 -> 289390 bytes lab1/train.png | Bin 0 -> 317605 bytes 5 files changed, 3446 insertions(+) create mode 100644 lab1/Lab01_Report.md create mode 100644 lab1/Untitled (1).ipynb create mode 100644 lab1/lab1.xlsx create mode 100644 lab1/train(2).png create mode 100644 lab1/train.png diff --git a/lab1/Lab01_Report.md b/lab1/Lab01_Report.md new file mode 100644 index 0000000..ceffa5f --- /dev/null +++ b/lab1/Lab01_Report.md @@ -0,0 +1,2150 @@ +# Лабораторная работа №1 +### Бинарная классификация фактографических данных +--- +Выполнила: Мачулина Дарья +Группа: А-02-22 +Вариант 9 + +--- +### 1. Создать новый ноутбук (Notebook) и импортировать необходимые для работы библиотеки и модули +```python +import numpy as np + +# `ребуемые 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 plt +``` +Для отображения на графике области принятия решения - готовую функцию `plot_2d_separator`, которой нужно передать на вход объект `classifier` – модель классификатора и `X` – массив входных данных: + +```python +def 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(()) +``` +--- +### 2. Загрузить данные в соответствии с вариантом и вывести первые 15 точек с метками классaа + + +```python +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) +``` + +```python +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] + +--- +### 3. Отображение на графике сгенерированных данных +```python +plt.scatter (X[:,0], X[:,1], c=y) +plt.show +``` +![[1.png]] + +--- +### 4. Разбиение выборки на тестовое и обучающее множества. Отображение выборок на графиках +```python +X_train, X_test, y_train, y_test = train_test_split(X, y, test_size = 0.25, random_state = 1) +``` + +**Обучающая выборка** +```python +plt.figure(figsize=(7, 5)) +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() +``` +![[train.png]] + +**Тестовая выборка** + +```python +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() +``` + +![[test.png]] + + +--- +### 5. Реализация модели классификации: метод k-ближайших соседей + +**n_neighbours = 1** +```python +knn = KNeighborsClassifier(n_neighbors=1, metric = 'euclidean') +knn.fit(X_train, y_train) +prediction = knn.predict(X_test) +``` +**Оценка качества модели**: +- Предсказанные и истинные значения +```python +print ('Prediction and test: ') +print (prediction) +print (y_test) +``` +Prediction and test: +[0 1 1 0 1 1 1 1 1 0 0 1 0 0 1 0 0 0 1 1 0 0 1 1 1 0 0 0 1 0 1 1 0 1 0 1 0 + 1 0 1 1 1 1 1 1 1 1 1 1 1 1 0 0 1 1 1 1 1 1 1 0 0 0 1 1 1 1 1 1 1 0 1 1 0 + 1 0 0 0 0 0 0 1 0 0 0 1 1 0 0 1 0 0 0 1 1 0 1 1 0 0 1 1 1 1 1 1 0 0 0 0 0 + 0 0 1 0 0 0 1 1 1 0 0 1 0 1 1 1 1 1 1 1 0 0 0 1 0 0 0 1 0 0 1 1 0 0 1 0 1 + 1 1 0 0 1 0 0 0 1 1 0 0 0 0 0 0 1 0 1 0 1 1 0 1 0 1 0 1 0 1 0 0 0 1 1 1 1 + 1 1 1 0 1 1 0 1 1 1 0 0 1 0 1 0 0 1 0 1 0 0 0 0 1 0 0 1 0 1 1 1 0 0 1 1 0 + 0 0 1 1 1 0 0 0 1 0 1 1 1 1 0 1 1 1 0 0 0 1 1 0 0 0 0 0] + +[0 0 0 0 1 0 0 0 1 0 0 1 0 0 1 0 0 0 0 1 0 0 0 1 1 0 0 0 1 0 1 1 0 1 0 1 1 + 1 0 1 1 1 1 1 0 1 0 1 1 0 1 0 0 1 1 1 1 0 1 1 1 0 0 1 0 1 0 0 1 1 1 1 1 0 + 1 0 0 0 0 0 0 1 0 0 0 1 1 0 1 1 0 0 0 1 1 1 1 1 0 0 1 1 1 1 1 1 1 0 0 0 1 + 0 0 1 0 0 0 1 1 1 0 0 1 0 1 1 0 1 0 0 1 0 0 0 1 0 0 0 0 1 0 1 1 1 0 1 1 1 + 1 1 0 0 1 0 0 1 1 1 0 0 0 0 0 0 1 1 1 1 0 1 0 1 1 1 0 0 0 0 0 1 0 1 0 1 1 + 1 1 1 1 1 0 0 1 0 1 0 0 1 1 0 0 1 1 0 1 0 0 0 0 1 0 1 1 0 1 0 0 0 1 1 1 0 + 0 1 0 0 1 0 0 0 0 1 1 1 0 1 1 1 1 1 0 0 0 1 1 0 0 0 0 0] + +- Матрица неточностей +```python +print ('Confusion matrix: ') +print (confusion_matrix(y_test, prediction)) +``` +Confusion matrix: +[[97 31] +[23 99]]] + +- Оценка аккуратности классификации +```python +print ('Accuracy score: ', accuracy_score(prediction, y_test)) +``` +Accuracy score: 0.784 + +- Оценка показателей полноты, точности и f-1 меры +```python +print(classification_report(y_test, prediction)) +``` + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + +
precisionrecallf1-scoresupport
00.810.760.78128
10.760.810.79122
accuracy 0.78250
macro avg0.780.780.78250
weighted avg0.790.780.78250
+ +- Оценка показателя AUC ROC +```python +roc_auc_score(y_test, prediction) +``` +0.7846439549180328 + +- Отображение области принятия решений по каждому классу +```python +plt.xlabel("first feature") +plt.ylabel("second feature") +plot_2d_separator(knn, X, fill=True) +plt.scatter(X[:, 0], X[:, 1], c=y, s=70) +``` +![[RS1.png]] + +**n_neighbours = 3** +```python +knn = KNeighborsClassifier(n_neighbors=3, metric = 'euclidean') +knn.fit(X_train, y_train) +prediction = knn.predict(X_test) +``` +**Оценка качества модели**: +- Предсказанные и истинные значения +```python +print ('Prediction and test: ') +print (prediction) +print (y_test) +``` +Prediction and test: +[0 1 1 1 1 1 1 1 1 0 0 1 0 0 1 0 0 0 1 1 0 0 1 1 1 0 0 0 1 0 1 1 0 1 0 1 1 + 1 0 1 1 1 1 1 1 1 1 1 1 1 1 0 0 1 1 1 1 1 1 1 1 0 0 1 1 1 1 1 1 1 1 1 1 0 + 1 0 0 1 0 0 0 1 0 0 0 1 1 0 0 1 0 0 0 1 1 0 1 1 0 0 1 1 1 1 1 1 1 0 0 0 1 + 0 0 1 0 0 0 1 1 1 0 0 1 0 1 1 0 1 1 1 1 0 0 0 1 0 0 0 1 1 1 1 1 0 0 1 1 1 + 1 1 0 0 1 0 0 1 1 1 0 0 0 0 0 0 1 1 1 0 1 1 0 1 1 1 0 1 0 1 0 1 0 1 1 1 1 + 1 1 1 0 1 1 0 0 1 1 0 0 1 1 1 0 0 1 0 1 0 0 0 0 1 0 1 1 0 1 0 0 0 1 1 1 0 + 0 1 1 1 1 0 0 0 1 0 1 1 0 1 1 1 1 1 0 0 0 1 1 0 0 1 0 0] + +[0 0 0 0 1 0 0 0 1 0 0 1 0 0 1 0 0 0 0 1 0 0 0 1 1 0 0 0 1 0 1 1 0 1 0 1 1 + 1 0 1 1 1 1 1 0 1 0 1 1 0 1 0 0 1 1 1 1 0 1 1 1 0 0 1 0 1 0 0 1 1 1 1 1 0 + 1 0 0 0 0 0 0 1 0 0 0 1 1 0 1 1 0 0 0 1 1 1 1 1 0 0 1 1 1 1 1 1 1 0 0 0 1 + 0 0 1 0 0 0 1 1 1 0 0 1 0 1 1 0 1 0 0 1 0 0 0 1 0 0 0 0 1 0 1 1 1 0 1 1 1 + 1 1 0 0 1 0 0 1 1 1 0 0 0 0 0 0 1 1 1 1 0 1 0 1 1 1 0 0 0 0 0 1 0 1 0 1 1 + 1 1 1 1 1 0 0 1 0 1 0 0 1 1 0 0 1 1 0 1 0 0 0 0 1 0 1 1 0 1 0 0 0 1 1 1 0 + 0 1 0 0 1 0 0 0 0 1 1 1 0 1 1 1 1 1 0 0 0 1 1 0 0 0 0 0] + +- Матрица неточностей +```python +print ('Confusion matrix: ') +print (confusion_matrix(y_test, prediction)) +``` +Confusion matrix: +[[97 31] +[8 114]] + +- Оценка аккуратности классификации +```python +print ('Accuracy score: ', accuracy_score(prediction, y_test)) +``` +Accuracy score: 0.844 + +- Оценка показателей полноты, точности и f-1 меры +```python +print(classification_report(y_test, prediction)) +``` + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + +
precisionrecallf1-scoresupport
00.920.760.83128
10.790.930.85122
accuracy 0.84250
macro avg0.860.850.84250
weighted avg0.860.840.84250
+ +- Оценка показателя AUC ROC +```python +roc_auc_score(y_test, prediction) +``` +0.8461193647540983 + +- Отображение области принятия решений по каждому классу +```python +plt.xlabel("first feature") +plt.ylabel("second feature") +plot_2d_separator(knn, X, fill=True) +plt.scatter(X[:, 0], X[:, 1], c=y, s=70) +``` +![[RS3.png]] + + +**n_neighbours = 9** +```python +knn = KNeighborsClassifier(n_neighbors=9, metric = 'euclidean') +knn.fit(X_train, y_train) +prediction = knn.predict(X_test) +``` +**Оценка качества модели**: +- Предсказанные и истинные значения +```python +print ('Prediction and test: ') +print (prediction) +print (y_test) +``` +Prediction and test: +[0 1 1 0 1 1 1 1 1 0 0 1 0 0 1 0 0 0 1 1 0 0 1 1 1 0 0 0 1 0 1 1 0 1 0 1 1 + 1 0 1 1 1 1 1 1 1 1 1 1 1 1 0 0 1 1 1 1 1 1 1 1 0 1 1 1 1 1 1 1 1 1 1 1 0 + 1 0 0 1 0 0 0 1 0 0 0 1 1 0 1 1 0 0 0 1 1 0 1 1 0 0 1 1 1 1 1 1 1 0 0 0 1 + 0 0 1 0 0 0 1 1 1 0 0 1 0 1 1 0 1 1 1 1 0 0 0 1 0 0 0 1 1 1 1 1 1 0 1 1 1 + 1 1 0 0 1 0 0 1 1 1 0 0 0 0 0 0 1 1 1 1 1 1 0 1 1 1 0 1 0 1 0 1 0 1 1 1 1 + 1 1 1 0 1 1 0 1 1 1 0 0 1 1 0 0 1 1 0 1 0 0 0 0 1 0 1 1 0 1 0 0 0 1 1 1 0 + 0 1 1 1 1 0 0 0 1 1 1 1 1 1 1 1 1 1 0 0 0 1 1 0 0 1 0 0] + +[0 0 0 0 1 0 0 0 1 0 0 1 0 0 1 0 0 0 0 1 0 0 0 1 1 0 0 0 1 0 1 1 0 1 0 1 1 + 1 0 1 1 1 1 1 0 1 0 1 1 0 1 0 0 1 1 1 1 0 1 1 1 0 0 1 0 1 0 0 1 1 1 1 1 0 + 1 0 0 0 0 0 0 1 0 0 0 1 1 0 1 1 0 0 0 1 1 1 1 1 0 0 1 1 1 1 1 1 1 0 0 0 1 + 0 0 1 0 0 0 1 1 1 0 0 1 0 1 1 0 1 0 0 1 0 0 0 1 0 0 0 0 1 0 1 1 1 0 1 1 1 + 1 1 0 0 1 0 0 1 1 1 0 0 0 0 0 0 1 1 1 1 0 1 0 1 1 1 0 0 0 0 0 1 0 1 0 1 1 + 1 1 1 1 1 0 0 1 0 1 0 0 1 1 0 0 1 1 0 1 0 0 0 0 1 0 1 1 0 1 0 0 0 1 1 1 0 + 0 1 0 0 1 0 0 0 0 1 1 1 0 1 1 1 1 1 0 0 0 1 1 0 0 0 0 0] + +- Матрица неточностей +```python +print ('Confusion matrix: ') +print (confusion_matrix(y_test, prediction)) +``` +Confusion matrix: +[[97 31] +[2 120]] + +- Оценка аккуратности классификации +```python +print ('Accuracy score: ', accuracy_score(prediction, y_test)) +``` +Accuracy score: 0.868 + +- Оценка показателей полноты, точности и f-1 меры +```python +print(classification_report(y_test, prediction)) +``` + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + +
precisionrecallf1-scoresupport
00.980.760.85128
10.790.980.88122
accuracy 0.87250
macro avg0.890.870.87250
weighted avg0.890.870.87250
+ +- Оценка показателя AUC ROC +```python +roc_auc_score(y_test, prediction) +``` +0.8707095286885246 + +- Отображение области принятия решений по каждому классу +```python +plt.xlabel("first feature") +plt.ylabel("second feature") +plot_2d_separator(knn, X, fill=True) +plt.scatter(X[:, 0], X[:, 1], c=y, s=70) +``` +![[RS9.png]] + +--- +### 6. Реализация модели классификации: наивный байесовский метод +```python +from sklearn.naive_bayes import GaussianNB +``` + +```python +gnb=GaussianNB() +gnb.fit(X_train, y_train) +prediction = gnb.predict(X_test) +``` + +**Оценка качества модели**: +- Предсказанные и истинные значения +```python +print ('Prediction and test: ') +print (prediction) +print (y_test) +``` +Prediction and test: +[0 1 1 0 1 1 1 1 1 0 0 1 0 0 1 0 0 1 1 1 0 0 1 1 1 0 0 0 1 0 1 1 0 1 0 1 1 + 1 0 1 1 1 1 1 1 1 1 1 1 1 1 0 0 1 1 1 1 1 1 1 1 0 1 1 1 1 1 0 1 1 1 1 1 0 + 1 0 0 1 0 0 0 1 0 0 0 1 1 0 1 1 0 0 0 1 1 1 1 1 0 0 1 1 1 1 1 1 1 0 0 0 1 + 0 0 1 1 0 0 1 1 1 0 0 1 0 1 1 0 1 1 1 1 0 0 0 1 0 0 0 1 1 1 1 1 1 0 1 1 1 + 1 1 0 0 1 0 0 1 1 1 0 0 0 0 0 0 1 1 1 1 1 1 0 1 1 1 0 1 0 0 0 1 0 1 1 1 1 + 1 1 1 1 1 1 0 1 1 1 0 0 1 1 1 0 1 1 0 1 0 0 0 0 1 0 1 1 0 1 0 0 0 1 1 1 0 + 0 1 1 1 1 0 0 0 1 1 1 1 1 1 1 1 1 1 0 0 0 1 1 0 0 1 0 0] + +[0 0 0 0 1 0 0 0 1 0 0 1 0 0 1 0 0 0 0 1 0 0 0 1 1 0 0 0 1 0 1 1 0 1 0 1 1 + 1 0 1 1 1 1 1 0 1 0 1 1 0 1 0 0 1 1 1 1 0 1 1 1 0 0 1 0 1 0 0 1 1 1 1 1 0 + 1 0 0 0 0 0 0 1 0 0 0 1 1 0 1 1 0 0 0 1 1 1 1 1 0 0 1 1 1 1 1 1 1 0 0 0 1 + 0 0 1 0 0 0 1 1 1 0 0 1 0 1 1 0 1 0 0 1 0 0 0 1 0 0 0 0 1 0 1 1 1 0 1 1 1 + 1 1 0 0 1 0 0 1 1 1 0 0 0 0 0 0 1 1 1 1 0 1 0 1 1 1 0 0 0 0 0 1 0 1 0 1 1 + 1 1 1 1 1 0 0 1 0 1 0 0 1 1 0 0 1 1 0 1 0 0 0 0 1 0 1 1 0 1 0 0 0 1 1 1 0 + 0 1 0 0 1 0 0 0 0 1 1 1 0 1 1 1 1 1 0 0 0 1 1 0 0 0 0 0] + +- Матрица неточностей +```python +print ('Confusion matrix: ') +print (confusion_matrix(y_test, prediction)) +``` +Confusion matrix: +[[96 32] +[0 122]] + +- Оценка аккуратности классификации +```python +print ('Accuracy score: ', accuracy_score(prediction, y_test)) +``` +Accuracy score: 0.872 + +- Оценка показателей полноты, точности и f-1 меры +```python +print(classification_report(y_test, prediction)) +``` + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + +
precisionrecallf1-scoresupport
01.000.750.86128
10.791.000.88122
accuracy 0.87250
macro avg0.900.880.87250
weighted avg0.900.870.87250
+ +- Оценка показателя AUC ROC +```python +roc_auc_score(y_test, prediction) +``` +0.875 + +- Отображение области принятия решений по каждому классу +```python +plt.xlabel("first feature") +plt.ylabel("second feature") +plot_2d_separator(gnb, X, fill=True) +plt.scatter(X[:, 0], X[:, 1], c=y, s=70) +``` +![[NB.png]] + +--- +### 7. Реализация модели классификации: метод "Случайный лес" + +**n_estimators = 5** + +```python +from sklearn.ensemble import RandomForestClassifier +``` + +```python +rf=RandomForestClassifier(n_estimators=5,random_state=42) +rf.fit(X_train, y_train) +prediction = rf.predict(X_test) +``` + +**Оценка качества модели**: +- Предсказанные и истинные значения +```python +print ('Prediction and test: ') +print (prediction) +print (y_test) +``` +Prediction and test: +[0 1 1 0 1 1 1 1 1 0 0 1 0 0 1 0 0 0 1 1 0 0 0 1 1 0 0 0 1 0 1 1 0 1 0 1 1 + 1 0 1 1 1 1 1 1 1 1 1 1 1 1 0 0 1 1 1 1 1 1 1 1 0 0 1 1 1 1 0 1 1 1 1 1 0 + 1 0 0 1 0 0 0 1 0 0 0 1 1 0 0 1 0 0 0 1 1 0 1 1 0 0 1 0 1 1 1 1 1 0 0 0 1 + 0 0 1 0 0 0 1 1 1 0 0 1 0 1 1 0 1 0 1 1 0 0 0 1 0 0 0 1 0 1 1 1 1 0 1 1 1 + 1 1 0 0 1 0 0 0 1 1 0 0 0 0 0 0 1 1 1 0 1 1 0 1 0 1 0 1 0 0 0 1 0 1 1 1 1 + 1 1 1 0 1 1 0 0 1 1 0 0 1 1 0 0 0 1 0 1 0 0 0 0 0 0 1 1 0 1 0 0 0 1 1 1 0 + 0 1 1 1 1 0 0 0 1 1 1 1 0 1 1 1 0 1 0 0 0 1 1 0 0 1 0 0] + +[0 0 0 0 1 0 0 0 1 0 0 1 0 0 1 0 0 0 0 1 0 0 0 1 1 0 0 0 1 0 1 1 0 1 0 1 1 + 1 0 1 1 1 1 1 0 1 0 1 1 0 1 0 0 1 1 1 1 0 1 1 1 0 0 1 0 1 0 0 1 1 1 1 1 0 + 1 0 0 0 0 0 0 1 0 0 0 1 1 0 1 1 0 0 0 1 1 1 1 1 0 0 1 1 1 1 1 1 1 0 0 0 1 + 0 0 1 0 0 0 1 1 1 0 0 1 0 1 1 0 1 0 0 1 0 0 0 1 0 0 0 0 1 0 1 1 1 0 1 1 1 + 1 1 0 0 1 0 0 1 1 1 0 0 0 0 0 0 1 1 1 1 0 1 0 1 1 1 0 0 0 0 0 1 0 1 0 1 1 + 1 1 1 1 1 0 0 1 0 1 0 0 1 1 0 0 1 1 0 1 0 0 0 0 1 0 1 1 0 1 0 0 0 1 1 1 0 + 0 1 0 0 1 0 0 0 0 1 1 1 0 1 1 1 1 1 0 0 0 1 1 0 0 0 0 0] + +- Матрица неточностей +```python +print ('Confusion matrix: ') +print (confusion_matrix(y_test, prediction)) +``` +Confusion matrix: +[[103 25] +[12 110]] + +- Оценка аккуратности классификации +```python +print ('Accuracy score: ', accuracy_score(prediction, y_test)) +``` +Accuracy score: 0.852 + +- Оценка показателей полноты, точности и f-1 меры +```python +print(classification_report(y_test, prediction)) +``` + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + +
precisionrecallf1-scoresupport
00.900.800.85128
10.810.900.86122
accuracy 0.85250
macro avg0.860.850.85250
weighted avg0.860.850.85250
+ +- Оценка показателя AUC ROC +```python +roc_auc_score(y_test, prediction) +``` +0.8531634221311475 + +- Отображение области принятия решений по каждому классу +```python +plt.xlabel("first feature") +plt.ylabel("second feature") +plot_2d_separator(rf, X, fill=True) +plt.scatter(X[:, 0], X[:, 1], c=y, s=70) +``` +![[RF5.png]] + + + +**n_estimators = 15** + +```python +from sklearn.ensemble import RandomForestClassifier +``` + +```python +rf=RandomForestClassifier(n_estimators=15,random_state=42) +rf.fit(X_train, y_train) +prediction = rf.predict(X_test) +``` + +**Оценка качества модели**: +- Предсказанные и истинные значения +```python +print ('Prediction and test: ') +print (prediction) +print (y_test) +``` +Prediction and test: +[0 1 1 0 1 1 1 1 1 0 0 1 0 0 1 0 0 0 1 1 0 0 0 1 1 0 0 0 1 0 1 1 0 1 0 1 1 + 1 0 1 1 1 1 1 1 1 1 1 1 1 1 0 0 1 1 1 1 1 1 1 1 0 0 1 0 1 1 0 1 1 1 1 1 0 + 1 0 0 1 0 0 0 1 0 0 0 1 1 0 1 1 0 0 0 1 1 0 1 1 0 0 1 1 1 1 1 1 1 0 0 0 1 + 0 0 1 0 0 0 1 1 1 0 0 1 0 1 1 0 1 0 1 1 0 0 0 1 0 0 0 1 1 1 1 1 1 0 1 1 1 + 1 1 0 0 1 0 0 0 1 1 0 0 0 0 0 0 1 1 1 1 1 1 0 1 1 1 0 1 0 0 0 1 0 1 1 1 1 + 1 1 1 0 1 1 0 0 1 1 0 0 1 1 0 0 0 1 0 1 0 0 0 0 0 0 1 1 0 1 0 0 0 1 1 1 0 + 0 1 1 1 1 0 0 0 1 1 1 1 0 1 1 1 1 1 0 0 0 1 1 0 0 1 0 0] + +[0 0 0 0 1 0 0 0 1 0 0 1 0 0 1 0 0 0 0 1 0 0 0 1 1 0 0 0 1 0 1 1 0 1 0 1 1 + 1 0 1 1 1 1 1 0 1 0 1 1 0 1 0 0 1 1 1 1 0 1 1 1 0 0 1 0 1 0 0 1 1 1 1 1 0 + 1 0 0 0 0 0 0 1 0 0 0 1 1 0 1 1 0 0 0 1 1 1 1 1 0 0 1 1 1 1 1 1 1 0 0 0 1 + 0 0 1 0 0 0 1 1 1 0 0 1 0 1 1 0 1 0 0 1 0 0 0 1 0 0 0 0 1 0 1 1 1 0 1 1 1 + 1 1 0 0 1 0 0 1 1 1 0 0 0 0 0 0 1 1 1 1 0 1 0 1 1 1 0 0 0 0 0 1 0 1 0 1 1 + 1 1 1 1 1 0 0 1 0 1 0 0 1 1 0 0 1 1 0 1 0 0 0 0 1 0 1 1 0 1 0 0 0 1 1 1 0 + 0 1 0 0 1 0 0 0 0 1 1 1 0 1 1 1 1 1 0 0 0 1 1 0 0 0 0 0] + +- Матрица неточностей +```python +print ('Confusion matrix: ') +print (confusion_matrix(y_test, prediction)) +``` +Confusion matrix: +[[104 24] +[6 116]] + +- Оценка аккуратности классификации +```python +print ('Accuracy score: ', accuracy_score(prediction, y_test)) +``` +Accuracy score: 0.88 + +- Оценка показателей полноты, точности и f-1 меры +```python +print(classification_report(y_test, prediction)) +``` + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + +
precisionrecallf1-scoresupport
00.950.810.87128
10.830.950.89122
accuracy 0.88250
macro avg0.890.880.88250
weighted avg0.890.880.88250
+ +- Оценка показателя AUC ROC +```python +roc_auc_score(y_test, prediction) +``` +0.8816598360655737 + +- Отображение области принятия решений по каждому классу +```python +plt.xlabel("first feature") +plt.ylabel("second feature") +plot_2d_separator(rf, X, fill=True) +plt.scatter(X[:, 0], X[:, 1], c=y, s=70) +``` +![[RF15.png]] + +**n_estimators = 50** + +```python +from sklearn.ensemble import RandomForestClassifier +``` + +```python +rf=RandomForestClassifier(n_estimators=50,random_state=42) +rf.fit(X_train, y_train) +prediction = rf.predict(X_test) +``` + +**Оценка качества модели**: +- Предсказанные и истинные значения +```python +print ('Prediction and test: ') +print (prediction) +print (y_test) +``` +Prediction and test: +[0 1 1 0 1 1 1 1 1 0 0 1 0 0 1 0 0 0 1 1 0 0 0 1 1 0 0 0 1 0 1 1 0 1 0 1 1 + 1 0 1 1 1 1 1 1 1 1 1 1 1 1 0 0 1 1 1 1 1 1 1 1 0 0 1 0 1 1 0 1 1 1 1 1 0 + 1 0 0 1 0 0 0 1 0 0 0 1 1 0 1 1 0 0 0 1 1 0 1 1 0 0 1 1 1 1 1 1 1 0 0 0 1 + 0 0 1 0 0 0 1 1 1 0 0 1 0 1 1 0 1 0 1 1 0 0 0 1 0 0 0 1 1 1 1 1 1 0 1 1 1 + 1 1 0 0 1 0 0 0 1 1 0 0 0 0 0 0 1 1 1 0 1 1 0 1 1 1 0 1 0 0 0 1 0 1 1 1 1 + 1 1 1 0 1 1 0 0 1 1 0 0 1 1 0 0 0 1 0 1 0 0 0 0 0 0 1 1 0 1 0 0 0 1 1 1 0 + 0 1 1 1 1 0 0 0 1 1 1 1 0 1 1 1 1 1 0 0 0 1 1 0 0 1 0 0] + +[0 0 0 0 1 0 0 0 1 0 0 1 0 0 1 0 0 0 0 1 0 0 0 1 1 0 0 0 1 0 1 1 0 1 0 1 1 + 1 0 1 1 1 1 1 0 1 0 1 1 0 1 0 0 1 1 1 1 0 1 1 1 0 0 1 0 1 0 0 1 1 1 1 1 0 + 1 0 0 0 0 0 0 1 0 0 0 1 1 0 1 1 0 0 0 1 1 1 1 1 0 0 1 1 1 1 1 1 1 0 0 0 1 + 0 0 1 0 0 0 1 1 1 0 0 1 0 1 1 0 1 0 0 1 0 0 0 1 0 0 0 0 1 0 1 1 1 0 1 1 1 + 1 1 0 0 1 0 0 1 1 1 0 0 0 0 0 0 1 1 1 1 0 1 0 1 1 1 0 0 0 0 0 1 0 1 0 1 1 + 1 1 1 1 1 0 0 1 0 1 0 0 1 1 0 0 1 1 0 1 0 0 0 0 1 0 1 1 0 1 0 0 0 1 1 1 0 + 0 1 0 0 1 0 0 0 0 1 1 1 0 1 1 1 1 1 0 0 0 1 1 0 0 0 0 0] + +- Матрица неточностей +```python +print ('Confusion matrix: ') +print (confusion_matrix(y_test, prediction)) +``` +Confusion matrix: +[[104 24] +[7 115]] + +- Оценка аккуратности классификации +```python +print ('Accuracy score: ', accuracy_score(prediction, y_test)) +``` +Accuracy score: 0.876 + +- Оценка показателей полноты, точности и f-1 меры +```python +print(classification_report(y_test, prediction)) +``` + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + +
precisionrecallf1-scoresupport
00.940.810.87128
10.830.940.88122
accuracy 0.88250
macro avg0.880.880.88250
weighted avg0.880.880.88250
+ +- Оценка показателя AUC ROC +```python +roc_auc_score(y_test, prediction) +``` +0.8775614754098361 + +- Отображение области принятия решений по каждому классу +```python +plt.xlabel("first feature") +plt.ylabel("second feature") +plot_2d_separator(rf, X, fill=True) +plt.scatter(X[:, 0], X[:, 1], c=y, s=70) +``` +![[RF50.png]] + + +### 8. Исследование для Random State = 2 +![[train(2).png]] + +![[test(2).png]] + +**n_neighbours = 1** +**Оценка качества модели**: +- Предсказанные и истинные значения +Prediction and test: +[0 0 1 1 0 0 1 1 1 1 1 0 0 1 0 0 1 1 1 0 0 0 1 1 1 0 0 1 1 1 0 1 0 1 0 0 1 + 1 1 1 0 1 0 0 1 1 1 1 1 1 0 0 0 1 0 1 1 1 1 1 0 1 1 0 0 0 1 0 0 0 1 1 0 0 + 0 1 1 0 0 1 1 0 0 0 1 1 0 0 0 0 0 1 0 1 1 1 1 0 1 1 1 0 0 1 0 0 1 0 1 0 1 + 1 0 1 1 1 1 1 1 1 1 1 1 1 0 1 1 1 1 0 0 1 1 0 1 0 0 0 0 0 1 1 1 1 1 1 1 0 + 1 0 1 1 0 0 1 1 1 0 1 1 0 0 1 1 1 1 1 0 0 0 0 1 0 0 1 1 1 1 1 0 0 0 1 1 1 + 0 0 1 1 0 1 0 1 0 1 1 1 1 0 0 0 1 1 1 1 0 0 1 1 1 0 1 1 1 1 0 0 0 0 1 1 1 + 0 1 1 1 0 0 1 1 0 0 1 0 0 1 1 1 0 1 1 1 1 1 1 0 0 1 1 1] + +[0 0 1 0 0 0 0 1 1 1 1 0 0 1 0 0 1 1 1 0 0 0 1 1 1 0 1 1 0 1 0 1 0 1 0 0 1 + 1 1 0 0 1 0 1 1 1 1 0 1 0 0 0 0 1 0 1 1 1 1 1 0 1 1 0 0 0 1 0 0 0 1 1 1 0 + 0 1 1 1 0 1 1 0 0 0 0 1 0 0 0 0 1 1 0 1 1 1 1 0 1 1 0 0 0 1 0 0 1 0 0 0 1 + 1 0 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 0 0 1 0 0 1 0 1 0 0 0 0 1 0 0 1 1 1 0 + 1 1 1 0 1 0 1 1 1 0 1 1 0 0 1 1 1 0 1 1 0 0 1 1 1 0 0 1 1 1 0 0 0 0 1 1 1 + 0 0 1 1 0 1 0 1 0 0 1 0 1 0 0 0 0 0 1 1 1 0 1 1 1 0 1 1 1 1 0 0 0 0 1 1 0 + 0 1 1 1 0 0 1 1 0 0 1 0 0 0 1 1 1 1 1 0 1 0 1 0 0 1 1 1] + +- Матрица неточностей +Confusion matrix: +[[89 25] +[14 122]]] + +- Оценка аккуратности классификации +Accuracy score: 0.844 + +- Оценка показателей полноты, точности и f-1 меры + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + +
precisionrecallf1-scoresupport
00.860.780.82114
10.830.900.86136
accuracy 0.84250
macro avg0.850.840.84250
weighted avg0.850.840.84250
+ + +- Оценка показателя AUC ROC +0.8388802889576883 + +- Отображение области принятия решений по каждому классу +![[RS1(2).png]] + +**n_neighbours = 3** +**Оценка качества модели**: +- Предсказанные и истинные значения +Prediction and test: +[0 0 1 1 0 0 1 1 1 1 1 0 0 1 0 0 1 1 1 0 0 0 1 1 1 0 1 1 1 1 0 1 0 1 0 0 1 + 1 1 1 0 1 0 0 1 1 1 1 1 1 0 0 0 1 0 1 1 1 1 1 1 1 1 0 0 0 1 0 0 0 1 1 1 0 + 0 1 1 1 0 1 1 0 0 0 1 1 0 0 0 0 1 1 0 1 1 0 1 0 1 1 1 0 0 1 0 0 1 0 1 0 1 + 1 0 1 1 1 1 1 1 1 1 1 1 1 0 1 1 1 1 0 0 1 1 0 1 0 0 0 0 0 1 1 1 0 1 1 1 0 + 1 1 1 1 1 0 1 1 1 0 1 1 0 0 1 1 1 1 1 0 0 0 1 1 0 0 1 1 1 1 0 0 0 0 1 1 1 + 0 0 1 1 0 1 0 1 1 1 1 1 1 0 0 0 1 1 1 1 0 0 1 1 1 0 1 1 1 1 0 1 0 0 1 0 1 + 0 1 1 1 0 0 1 1 0 0 1 0 0 1 1 1 0 1 1 0 1 1 1 0 0 1 1 1] +[0 0 1 0 0 0 0 1 1 1 1 0 0 1 0 0 1 1 1 0 0 0 1 1 1 0 1 1 0 1 0 1 0 1 0 0 1 + 1 1 0 0 1 0 1 1 1 1 0 1 0 0 0 0 1 0 1 1 1 1 1 0 1 1 0 0 0 1 0 0 0 1 1 1 0 + 0 1 1 1 0 1 1 0 0 0 0 1 0 0 0 0 1 1 0 1 1 1 1 0 1 1 0 0 0 1 0 0 1 0 0 0 1 + 1 0 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 0 0 1 0 0 1 0 1 0 0 0 0 1 0 0 1 1 1 0 + 1 1 1 0 1 0 1 1 1 0 1 1 0 0 1 1 1 0 1 1 0 0 1 1 1 0 0 1 1 1 0 0 0 0 1 1 1 + 0 0 1 1 0 1 0 1 0 0 1 0 1 0 0 0 0 0 1 1 1 0 1 1 1 0 1 1 1 1 0 0 0 0 1 1 0 + 0 1 1 1 0 0 1 1 0 0 1 0 0 0 1 1 1 1 1 0 1 0 1 0 0 1 1 1] + +- Матрица неточностей +Confusion matrix: +[[89 25] +[9 127]]] + +- Оценка аккуратности классификации +Accuracy score: 0.864 + +- Оценка показателей полноты, точности и f-1 меры + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + +
precisionrecallf1-scoresupport
00.910.780.84114
10.840.930.88136
accuracy 0.86250
macro avg0.870.860.86250
weighted avg0.870.860.86250
+ +- Оценка показателя AUC ROC +0.8572626418988647 + +- Отображение области принятия решений по каждому классу +![[RS3(2).png]] + +**n_neighbours = 9** +**Оценка качества модели**: +- Предсказанные и истинные значения +Prediction and test: +[0 0 1 1 0 0 1 1 1 1 1 0 0 1 0 0 1 1 1 0 0 0 1 1 1 0 1 1 1 1 0 1 0 1 0 0 1 + 1 1 1 0 1 0 1 1 1 1 1 1 1 0 0 0 1 0 1 1 1 1 1 1 1 1 0 0 0 1 0 0 0 1 1 1 0 + 0 1 1 1 0 1 1 0 0 0 1 1 0 0 0 0 1 1 0 1 1 1 1 0 1 1 1 0 0 1 0 0 1 0 1 0 1 + 1 0 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 0 0 1 1 0 1 0 1 0 0 0 1 1 1 0 1 1 1 0 + 1 1 1 1 1 0 1 1 1 0 1 1 0 0 1 1 1 1 1 1 0 0 1 1 1 0 1 1 1 1 0 0 0 0 1 1 1 + 0 0 1 1 0 1 0 1 0 1 1 1 1 0 0 0 1 1 1 1 1 0 1 1 1 0 1 1 1 1 0 1 0 0 1 1 1 + 0 1 1 1 0 0 1 1 0 0 1 0 0 1 1 1 0 1 1 1 1 1 1 0 0 1 1 1] +[0 0 1 0 0 0 0 1 1 1 1 0 0 1 0 0 1 1 1 0 0 0 1 1 1 0 1 1 0 1 0 1 0 1 0 0 1 + 1 1 0 0 1 0 1 1 1 1 0 1 0 0 0 0 1 0 1 1 1 1 1 0 1 1 0 0 0 1 0 0 0 1 1 1 0 + 0 1 1 1 0 1 1 0 0 0 0 1 0 0 0 0 1 1 0 1 1 1 1 0 1 1 0 0 0 1 0 0 1 0 0 0 1 + 1 0 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 0 0 1 0 0 1 0 1 0 0 0 0 1 0 0 1 1 1 0 + 1 1 1 0 1 0 1 1 1 0 1 1 0 0 1 1 1 0 1 1 0 0 1 1 1 0 0 1 1 1 0 0 0 0 1 1 1 + 0 0 1 1 0 1 0 1 0 0 1 0 1 0 0 0 0 0 1 1 1 0 1 1 1 0 1 1 1 1 0 0 0 0 1 1 0 + 0 1 1 1 0 0 1 1 0 0 1 0 0 0 1 1 1 1 1 0 1 0 1 0 0 1 1 1] + +- Матрица неточностей +Confusion matrix: +[[89 25] +[1 135]]] + +- Оценка аккуратности классификации +Accuracy score: 0.896 + +- Оценка показателей полноты, точности и f-1 меры + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + +
precisionrecallf1-scoresupport
00.990.780.87114
10.840.990.91136
accuracy 0.90250
macro avg0.920.890.89250
weighted avg0.910.900.89250
+ + +- Оценка показателя AUC ROC +0.8866744066047471 + +- Отображение области принятия решений по каждому классу +![[RS9(2).png]] + +**GaussianNB** +**Оценка качества модели**: +- Предсказанные и истинные значения +Prediction and test: +[0 0 1 1 0 0 1 1 1 1 1 0 0 1 0 0 1 1 1 0 0 0 1 1 1 0 1 1 1 1 0 1 0 1 0 0 1 + 1 1 1 0 1 0 1 1 1 1 1 1 1 0 0 0 1 0 1 1 1 1 1 1 1 1 0 0 0 1 0 0 0 1 1 1 0 + 0 1 1 1 0 1 1 0 0 0 1 1 0 0 0 0 1 1 0 1 1 1 1 0 1 1 0 0 0 1 0 0 1 0 1 0 1 + 1 0 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 0 0 1 0 0 1 0 1 0 0 0 1 1 1 1 1 1 1 0 + 1 1 1 1 1 0 1 1 1 0 1 1 0 0 1 1 1 1 1 1 0 0 1 1 1 0 1 1 1 1 0 0 0 0 1 1 1 + 0 0 1 1 0 1 0 1 0 1 1 1 1 0 0 0 1 1 1 1 1 0 1 1 1 0 1 1 1 1 1 1 0 0 1 1 1 + 0 1 1 1 1 0 1 1 0 0 1 0 0 1 1 1 0 1 1 1 1 1 1 0 0 1 1 1] +[0 0 1 0 0 0 0 1 1 1 1 0 0 1 0 0 1 1 1 0 0 0 1 1 1 0 1 1 0 1 0 1 0 1 0 0 1 + 1 1 0 0 1 0 1 1 1 1 0 1 0 0 0 0 1 0 1 1 1 1 1 0 1 1 0 0 0 1 0 0 0 1 1 1 0 + 0 1 1 1 0 1 1 0 0 0 0 1 0 0 0 0 1 1 0 1 1 1 1 0 1 1 0 0 0 1 0 0 1 0 0 0 1 + 1 0 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 0 0 1 0 0 1 0 1 0 0 0 0 1 0 0 1 1 1 0 + 1 1 1 0 1 0 1 1 1 0 1 1 0 0 1 1 1 0 1 1 0 0 1 1 1 0 0 1 1 1 0 0 0 0 1 1 1 + 0 0 1 1 0 1 0 1 0 0 1 0 1 0 0 0 0 0 1 1 1 0 1 1 1 0 1 1 1 1 0 0 0 0 1 1 0 + 0 1 1 1 0 0 1 1 0 0 1 0 0 0 1 1 1 1 1 0 1 0 1 0 0 1 1 1] + +- Матрица неточностей +Confusion matrix: +[[88 26] +[1 135]]] + +- Оценка аккуратности классификации +Accuracy score: 0.892 + +- Оценка показателей полноты, точности и f-1 меры + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + +
precisionrecallf1-scoresupport
00.990.770.87114
10.840.990.91136
accuracy 0.89250
macro avg0.910.880.89250
weighted avg0.910.890.89250
+ + +- Оценка показателя AUC ROC +0.8822884416924665 + +- Отображение области принятия решений по каждому классу +![[NB(2).png]] + +**n_estimators = 5** +**Оценка качества модели**: +- Предсказанные и истинные значения +Prediction and test: +[0 0 1 1 0 0 1 1 1 0 1 0 0 1 0 0 1 1 1 0 0 0 1 1 0 0 1 1 1 1 0 1 0 1 0 0 1 + 1 1 0 0 1 0 1 1 1 1 1 1 1 0 0 0 1 0 1 1 1 1 1 1 1 0 0 0 0 1 0 0 0 1 1 1 0 + 0 1 1 1 0 1 1 0 0 0 1 1 0 0 0 0 1 1 0 1 1 1 1 0 1 1 0 0 0 1 0 0 1 0 1 0 1 + 1 0 1 1 1 1 0 1 1 1 1 1 1 0 1 1 1 1 0 0 1 0 0 1 0 1 0 0 0 1 1 1 0 1 1 1 0 + 1 1 1 1 1 0 1 1 1 0 1 1 0 0 1 1 1 1 1 0 0 0 1 1 0 0 1 1 1 1 0 0 0 0 1 1 1 + 0 0 1 1 0 1 0 1 0 1 1 1 1 0 0 0 1 1 0 1 0 0 1 1 1 0 1 1 1 1 1 1 0 0 1 1 1 + 0 1 1 1 0 0 1 1 0 0 1 0 0 1 1 1 0 1 1 1 1 1 1 0 0 1 1 1] +[0 0 1 0 0 0 0 1 1 1 1 0 0 1 0 0 1 1 1 0 0 0 1 1 1 0 1 1 0 1 0 1 0 1 0 0 1 + 1 1 0 0 1 0 1 1 1 1 0 1 0 0 0 0 1 0 1 1 1 1 1 0 1 1 0 0 0 1 0 0 0 1 1 1 0 + 0 1 1 1 0 1 1 0 0 0 0 1 0 0 0 0 1 1 0 1 1 1 1 0 1 1 0 0 0 1 0 0 1 0 0 0 1 + 1 0 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 0 0 1 0 0 1 0 1 0 0 0 0 1 0 0 1 1 1 0 + 1 1 1 0 1 0 1 1 1 0 1 1 0 0 1 1 1 0 1 1 0 0 1 1 1 0 0 1 1 1 0 0 0 0 1 1 1 + 0 0 1 1 0 1 0 1 0 0 1 0 1 0 0 0 0 0 1 1 1 0 1 1 1 0 1 1 1 1 0 0 0 0 1 1 0 + 0 1 1 1 0 0 1 1 0 0 1 0 0 0 1 1 1 1 1 0 1 0 1 0 0 1 1 1] + +- Матрица неточностей +Confusion matrix: +[[91 23] +[[[10 126]]] + +- Оценка аккуратности классификации +Accuracy score: 0.868 + +- Оценка показателей полноты, точности и f-1 меры + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + +
precisionrecallf1-scoresupport
00.900.800.85114
10.850.930.88136
accuracy 0.87250
macro avg0.870.860.87250
weighted avg0.870.870.87250
+ + +- Оценка показателя AUC ROC +0.862358101135191 + +- Отображение области принятия решений по каждому классу +![[RF5(2).png]] + +**n_estimators = 15** +**Оценка качества модели**: +- Предсказанные и истинные значения +Prediction and test: +[0 0 1 1 0 0 1 1 1 1 1 0 0 1 0 0 1 1 1 0 0 0 1 1 1 0 1 1 1 1 0 1 0 1 0 0 1 + 1 1 1 0 1 0 1 1 1 1 1 1 1 0 0 0 1 0 1 1 1 1 1 1 1 0 0 0 0 1 0 0 0 1 1 1 0 + 0 1 1 1 0 1 1 0 0 0 1 1 0 0 0 0 1 1 0 1 1 1 1 0 1 1 0 0 0 1 0 0 1 0 1 0 1 + 1 0 1 1 1 1 1 1 1 1 1 1 1 0 1 1 1 1 0 0 1 0 0 1 0 1 0 0 0 1 1 1 0 1 1 1 0 + 1 1 1 1 1 0 1 1 1 0 1 1 0 0 1 1 1 1 1 0 0 0 1 1 0 0 1 1 1 1 0 0 0 0 1 1 1 + 0 0 1 1 0 1 0 1 0 1 1 1 1 0 0 0 1 1 0 1 0 0 1 1 1 0 1 1 1 1 1 1 0 0 1 1 1 + 0 1 1 1 0 0 1 1 0 0 1 0 0 1 1 1 0 1 1 1 1 1 1 0 0 1 1 1] +[0 0 1 0 0 0 0 1 1 1 1 0 0 1 0 0 1 1 1 0 0 0 1 1 1 0 1 1 0 1 0 1 0 1 0 0 1 + 1 1 0 0 1 0 1 1 1 1 0 1 0 0 0 0 1 0 1 1 1 1 1 0 1 1 0 0 0 1 0 0 0 1 1 1 0 + 0 1 1 1 0 1 1 0 0 0 0 1 0 0 0 0 1 1 0 1 1 1 1 0 1 1 0 0 0 1 0 0 1 0 0 0 1 + 1 0 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 0 0 1 0 0 1 0 1 0 0 0 0 1 0 0 1 1 1 0 + 1 1 1 0 1 0 1 1 1 0 1 1 0 0 1 1 1 0 1 1 0 0 1 1 1 0 0 1 1 1 0 0 0 0 1 1 1 + 0 0 1 1 0 1 0 1 0 0 1 0 1 0 0 0 0 0 1 1 1 0 1 1 1 0 1 1 1 1 0 0 0 0 1 1 0 + 0 1 1 1 0 0 1 1 0 0 1 0 0 0 1 1 1 1 1 0 1 0 1 0 0 1 1 1] + +- Матрица неточностей +Confusion matrix: +[[90 24] +[7 129]]] + +- Оценка аккуратности классификации +Accuracy score: 0.876 + +- Оценка показателей полноты, точности и f-1 меры + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + +
precisionrecallf1-scoresupport
00.930.790.85114
10.840.950.89136
accuracy 0.88250
macro avg0.890.870.87250
weighted avg0.880.880.87250
+ + +- Оценка показателя AUC ROC +0.8690015479876161 + +- Отображение области принятия решений по каждому классу + + +**n_estimators = 50** +**Оценка качества модели**: +- Предсказанные и истинные значения +Prediction and test: +[0 0 1 1 0 0 1 1 1 1 1 0 0 1 0 0 1 1 1 0 0 0 1 1 1 0 1 1 1 1 0 1 0 1 0 0 1 + 1 1 1 0 1 0 1 1 1 1 1 1 1 0 0 0 1 0 1 1 1 1 1 1 1 0 0 0 0 1 0 0 0 1 1 1 0 + 0 1 1 1 0 1 1 0 0 0 1 1 0 0 0 0 1 1 0 1 1 1 1 0 1 1 0 0 0 1 0 0 1 0 1 0 1 + 1 0 1 1 1 1 1 1 1 1 1 1 1 0 1 1 1 1 0 0 1 0 0 1 0 1 0 0 0 1 1 1 0 1 1 1 0 + 1 1 1 1 1 0 1 1 1 0 1 1 0 0 1 1 1 1 1 0 0 0 1 1 0 0 1 1 1 1 0 0 0 0 1 1 1 + 0 0 1 1 0 1 0 1 0 1 1 1 1 0 0 0 1 1 0 1 0 0 1 1 1 0 1 1 1 1 1 1 0 0 1 1 1 + 0 1 1 1 0 0 1 1 0 0 1 0 0 1 1 1 0 1 1 1 1 1 1 0 0 1 1 1] +[0 0 1 0 0 0 0 1 1 1 1 0 0 1 0 0 1 1 1 0 0 0 1 1 1 0 1 1 0 1 0 1 0 1 0 0 1 + 1 1 0 0 1 0 1 1 1 1 0 1 0 0 0 0 1 0 1 1 1 1 1 0 1 1 0 0 0 1 0 0 0 1 1 1 0 + 0 1 1 1 0 1 1 0 0 0 0 1 0 0 0 0 1 1 0 1 1 1 1 0 1 1 0 0 0 1 0 0 1 0 0 0 1 + 1 0 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 0 0 1 0 0 1 0 1 0 0 0 0 1 0 0 1 1 1 0 + 1 1 1 0 1 0 1 1 1 0 1 1 0 0 1 1 1 0 1 1 0 0 1 1 1 0 0 1 1 1 0 0 0 0 1 1 1 + 0 0 1 1 0 1 0 1 0 0 1 0 1 0 0 0 0 0 1 1 1 0 1 1 1 0 1 1 1 1 0 0 0 0 1 1 0 + 0 1 1 1 0 0 1 1 0 0 1 0 0 0 1 1 1 1 1 0 1 0 1 0 0 1 1 1] + +- Матрица неточностей +Confusion matrix: +[[90 24] +[7 129]]] + +- Оценка аккуратности классификации +Accuracy score: 0.876 + +- Оценка показателей полноты, точности и f-1 меры + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + +
precisionrecallf1-scoresupport
00.930.790.85114
10.840.950.89136
accuracy 0.88250
macro avg0.890.870.87250
weighted avg0.880.880.87250
+ +- Оценка показателя AUC ROC +0.8690015479876161 + +- Отображение области принятия решений по каждому классу +![[RF50(2).png]] + + +### 9. Исследование для Random State = 3 +![[train(3).png]] +![[test(3).png]] + +**n_neighbours = 1** +**Оценка качества модели**: +- Предсказанные и истинные значения +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] + +- Матрица неточностей +Confusion matrix: +[[105 25] +[18 102]]] + +- Оценка аккуратности классификации +Accuracy score: 0.828 + +- Оценка показателей полноты, точности и f-1 меры + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + +
precisionrecallf1-scoresupport
00.850.810.83130
10.800.850.83120
accuracy 0.83250
macro avg0.830.830.83250
weighted avg0.830.830.83250
+ +- Оценка показателя AUC ROC +0.8288461538461539 + +- Отображение области принятия решений по каждому классу +![[RS1(3).png]] + +**n_neighbours = 3** +**Оценка качества модели**: +- Предсказанные и истинные значения +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] + +- Матрица неточностей +Confusion matrix: +[[104 26] +[6 114]]] + +- Оценка аккуратности классификации +Accuracy score: 0.872 + +- Оценка показателей полноты, точности и f-1 меры + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + +
precisionrecallf1-scoresupport
00.950.800.87130
10.810.950.88120
accuracy 0.87250
macro avg0.880.880.87250
weighted avg0.880.870.87250
+ +- Оценка показателя AUC ROC +0.875 + +- Отображение области принятия решений по каждому классу +![[RS3(3).png]] + +**n_neighbours = 9** +**Оценка качества модели**: +- Предсказанные и истинные значения +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] + +- Матрица неточностей +Confusion matrix: +[[100 30] +[3 117]]] + +- Оценка аккуратности классификации +Accuracy score: 0.868 + +- Оценка показателей полноты, точности и f-1 меры + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + +
precisionrecallf1-scoresupport
00.970.770.86130
10.800.970.88120
accuracy 0.87250
macro avg0.880.870.87250
weighted avg0.890.870.87250
+ +- Оценка показателя AUC ROC +0.8721153846153846 + +- Отображение области принятия решений по каждому классу +![[RS9(3).png]] + +**GaussianNB** +**Оценка качества модели**: +- Предсказанные и истинные значения +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] + +- Матрица неточностей +Confusion matrix: +[[107 23] +[1 119]]] + +- Оценка аккуратности классификации +Accuracy score: 0.904 + +- Оценка показателей полноты, точности и f-1 меры + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + +
precisionrecallf1-scoresupport
00.990.820.90130
10.840.990.91120
accuracy 0.30250
macro avg0.910.910.90250
weighted avg0.920.900.90250
+ +- Оценка показателя AUC ROC +0.9073717948717948 + +- Отображение области принятия решений по каждому классу +![[NB(3).png]] + +**n_estimators = 5** +**Оценка качества модели**: +- Предсказанные и истинные значения +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] +- Матрица неточностей +Confusion matrix: +[[107 23] +[[[[11 109]]] + +- Оценка аккуратности классификации +Accuracy score: 0.864 + +- Оценка показателей полноты, точности и f-1 меры + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + +
precisionrecallf1-scoresupport
00.910.820.86130
10.830.910.87120
accuracy 0.86250
macro avg0.870.870.86250
weighted avg0.870.860.86250
+ +- Оценка показателя AUC ROC +0.8657051282051281 + +- Отображение области принятия решений по каждому классу +![[RF5(2).png]] + +**n_estimators = 15** +**Оценка качества модели**: +- Предсказанные и истинные значения +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] + +- Матрица неточностей +Confusion matrix: +[[109 21] +[8 112]]] + +- Оценка аккуратности классификации +Accuracy score: 0.884 + +- Оценка показателей полноты, точности и f-1 меры + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + +
precisionrecallf1-scoresupport
00.930.840.88130
10.840.930.89120
accuracy 0.88250
macro avg0.890.890.88250
weighted avg0.890.880.87250
+ +- Оценка показателя AUC ROC +0.885897435897436 + +- Отображение области принятия решений по каждому классу +![[RF15(3).png]] + +**n_estimators = 50** +**Оценка качества модели**: +- Предсказанные и истинные значения +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] + +- Матрица неточностей +Confusion matrix: +[[110 20] +[9 111]]] + +- Оценка аккуратности классификации +Accuracy score: 0.884 + +- Оценка показателей полноты, точности и f-1 меры + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + +
precisionrecallf1-scoresupport
00.920.850.88130
10.850.930.88120
accuracy 0.88250
macro avg0.890.890.88250
weighted avg0.890.880.88250
+ +- Оценка показателя AUC ROC +0.885576923076923 + +- Отображение области принятия решений по каждому классу +![[RF50(3).png]] + + + +### ВЫВОД: + +По результатам трёх экспериментов наилучшими показателями качества обладает наивный байесовский метод - вне зависимости от разбиения выборки, он показывал стабильно высокие значения показателей качества (accuracy, precision, recall, f1-score и ROC AUC) без большого разброса между ними и их значениями между экспериментами. + +Также, высокие результаты показал RandomForest (n=15), и хотя значения показателей качества ниже, чем у наивного байесовского метода, различие метрик Accuracy и ROC AUC от эксперимента к эксперименту имеют меньший разброс, что говорит о более высокой стабильности метода diff --git a/lab1/Untitled (1).ipynb b/lab1/Untitled (1).ipynb new file mode 100644 index 0000000..39b719a --- /dev/null +++ b/lab1/Untitled (1).ipynb @@ -0,0 +1,1296 @@ +{ + "metadata": { + "kernelspec": { + "name": "python", + "display_name": "Python (Pyodide)", + "language": "python" + }, + "language_info": { + "codemirror_mode": { + "name": "python", + "version": 3 + }, + "file_extension": ".py", + "mimetype": "text/x-python", + "name": "python", + "nbconvert_exporter": "python", + "pygments_lexer": "ipython3", + "version": "3.8" + } + }, + "nbformat_minor": 5, + "nbformat": 4, + "cells": [ + { + "id": "4572253f-47a0-4c98-8852-cd8a0fa5c461", + "cell_type": "code", + "source": "import numpy as np\n\n# Требуемые модули из sklearn\nfrom sklearn.datasets import make_classification\nfrom sklearn.metrics import confusion_matrix, classification_report, accuracy_score, roc_auc_score\nfrom sklearn.model_selection import train_test_split\nfrom sklearn.neighbors import KNeighborsClassifier\n\n#Графики\nimport matplotlib.pyplot as plt", + "metadata": { + "trusted": true + }, + "outputs": [], + "execution_count": 1 + }, + { + "id": "d731e066-0f22-4bab-a620-7e437ea55d11", + "cell_type": "code", + "source": "def plot_2d_separator(classifier, X, fill=False, line=True, ax=None, eps=None):\n if eps is None:\n eps = 1.0 #X.std() / 2.\n x_min, x_max = X[:, 0].min() - eps, X[:, 0].max() + eps\n y_min, y_max = X[:, 1].min() - eps, X[:, 1].max() + eps\n xx = np.linspace(x_min, x_max, 100)\n yy = np.linspace(y_min, y_max, 100)\n X1, X2 = np.meshgrid(xx, yy)\n X_grid = np.c_[X1.ravel(), X2.ravel()]\n try:\n decision_values = classifier.decision_function(X_grid)\n levels = [0]\n fill_levels = [decision_values.min(), 0, decision_values.max()]\n except AttributeError:\n # no decision_function\n decision_values = classifier.predict_proba(X_grid)[:, 1]\n levels = [.5]\n fill_levels = [0, .5, 1]\n if ax is None:\n ax = plt.gca()\n if fill:\n ax.contourf(X1, X2, decision_values.reshape(X1.shape),\n levels=fill_levels, colors=['cyan', 'pink', 'yellow'])\n if line:\n ax.contour(X1, X2, decision_values.reshape(X1.shape), levels=levels, colors=\"black\")\n ax.set_xlim(x_min, x_max)\n ax.set_ylim(y_min, y_max)\n ax.set_xticks(())\n ax.set_yticks(())", + "metadata": { + "trusted": true + }, + "outputs": [], + "execution_count": 2 + }, + { + "id": "ea8112ad-501f-4afd-baa7-9a69395c5a38", + "cell_type": "code", + "source": "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)", + "metadata": { + "trusted": true + }, + "outputs": [], + "execution_count": 3 + }, + { + "id": "6ef2a9f4-4bcf-4123-8688-7dc5ea3a23ee", + "cell_type": "code", + "source": "print (\"Координаты точек: \") \nprint (X[:15])\nprint (\"Метки класса: \") \nprint (y[:15])", + "metadata": { + "trusted": true + }, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": "Координаты точек: \n[[ 1.48828264e+00 -7.10442604e-01]\n [-7.10253928e-01 6.93938341e-01]\n [ 5.33444250e-01 -1.31136377e+00]\n [ 1.08104452e+00 5.34466225e-01]\n [-3.97224728e-01 1.29783335e-01]\n [ 1.12862644e-01 5.10913913e-01]\n [ 7.13520454e-04 7.42926105e-01]\n [-1.50699375e+00 -1.51932200e+00]\n [-7.09257115e-01 4.58339246e-01]\n [-1.51395805e+00 -1.13202013e-01]\n [ 1.64173194e+00 5.62099713e-01]\n [-2.07311044e+00 -7.20098263e-01]\n [ 1.21634891e+00 4.34451064e-01]\n [-1.39209028e+00 5.71283980e-01]\n [ 4.57465767e-01 5.26568280e-01]]\nМетки класса: \n[0 1 0 1 0 1 0 0 1 0 1 0 1 1 1]\n" + } + ], + "execution_count": 4 + }, + { + "id": "52722b3e-1b24-4ca4-93b4-ef7a86aa9983", + "cell_type": "code", + "source": "plt.scatter (X[:,0], X[:,1], c=y)\nplt.show", + "metadata": { + "trusted": true + }, + "outputs": [ + { + "execution_count": 5, + "output_type": "execute_result", + "data": { + "text/plain": "" + }, + "metadata": {} + }, + { + "output_type": "display_data", + "data": { + "text/plain": "
", + "image/png": 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" + }, + "metadata": {} + } + ], + "execution_count": 5 + }, + { + "id": "f5f9365a-a487-400d-9cb7-27f0bdceedff", + "cell_type": "code", + "source": "X_train, X_test, y_train, y_test = train_test_split(X, y, test_size = 0.25, random_state = 3)", + "metadata": { + "trusted": true + }, + "outputs": [], + "execution_count": 6 + }, + { + "id": "c5e6c10b-86a4-45f0-887c-a9c1682018f0", + "cell_type": "code", + "source": "plt.figure(figsize=(7, 5))\n\n# Обучающая выборка\nplt.scatter(\n X_train[:, 0], X_train[:, 1],\n c=y_train,\n label=\"train\"\n)\n\nplt.title(\"Обучающая выборка\")\nplt.xlabel(\"x1\")\nplt.ylabel(\"x2\")\nplt.grid(True, alpha=0.3)\nplt.show()", + "metadata": { + "trusted": true + }, + "outputs": [ + { + "output_type": "display_data", + "data": { + "text/plain": "
", + "image/png": 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" + }, + "metadata": {} + } + ], + "execution_count": 7 + }, + { + "id": "ffd8e14d-1825-4a6a-894d-6aca3bf4d69f", + "cell_type": "code", + "source": "plt.figure(figsize=(7, 5))\n\n# Тестовая выборка\nplt.scatter(\n X_test[:, 0], X_test[:, 1],\n c=y_test, \n label=\"test\"\n)\n\nplt.title(\"Тестовая выборка\")\nplt.xlabel(\"x1\")\nplt.ylabel(\"x2\")\nplt.grid(True, alpha=0.3)\nplt.show()", + "metadata": { + "trusted": true + }, + "outputs": [ + { + "output_type": "display_data", + "data": { + "text/plain": "
", + "image/png": 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" + }, + "metadata": {} + } + ], + "execution_count": 8 + }, + { + "id": "505c396b-a837-4a7a-9924-2f3887fb4a82", + "cell_type": "code", + "source": "#RS_1", + "metadata": { + "trusted": true + }, + "outputs": [], + "execution_count": 9 + }, + { + "id": "ab5b2a09-6eb6-4b39-8b02-756b9afa8084", + "cell_type": "code", + "source": "knn = KNeighborsClassifier(n_neighbors=1, metric = 'euclidean')", + "metadata": { + "trusted": true + }, + "outputs": [], + "execution_count": 10 + }, + { + "id": "9e0dfcd4-f045-4c66-9f70-6ff6067e0809", + "cell_type": "code", + "source": "knn.fit(X_train, y_train)", + "metadata": { + "trusted": true + }, + "outputs": [ + { + "execution_count": 11, + "output_type": "execute_result", + "data": { + "text/plain": "KNeighborsClassifier(metric='euclidean', n_neighbors=1)", + "text/html": "
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.
" + }, + "metadata": {} + } + ], + "execution_count": 11 + }, + { + "id": "82f42e8a-6867-4042-9184-56e1beb00585", + "cell_type": "code", + "source": "prediction = knn.predict(X_test)", + "metadata": { + "trusted": true + }, + "outputs": [], + "execution_count": 12 + }, + { + "id": "857bc801-a975-44c2-94a1-513f90243480", + "cell_type": "code", + "source": "print ('Prediction and test: ')\nprint (prediction)\nprint (y_test)", + "metadata": { + "trusted": true + }, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": "Prediction and test: \n[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\n 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\n 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\n 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\n 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\n 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\n 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]\n[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\n 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\n 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\n 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\n 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\n 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\n 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]\n" + } + ], + "execution_count": 13 + }, + { + "id": "678d5592-8e14-4ac0-a985-393af82ce741", + "cell_type": "code", + "source": "print ('Confusion matrix: ')\nprint (confusion_matrix(y_test, prediction))", + "metadata": { + "trusted": true + }, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": "Confusion matrix: \n[[105 25]\n [ 18 102]]\n" + } + ], + "execution_count": 14 + }, + { + "id": "47a06468-dc56-49ae-a549-83154b3cd3b3", + "cell_type": "code", + "source": "print ('Accuracy score: ', accuracy_score(prediction, y_test))", + "metadata": { + "trusted": true + }, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": "Accuracy score: 0.828\n" + } + ], + "execution_count": 15 + }, + { + "id": "a72446bc-4d47-4d42-81b5-0c9aeede1fbf", + "cell_type": "code", + "source": "print(classification_report(y_test, prediction))", + "metadata": { + "trusted": true + }, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": " precision recall f1-score support\n\n 0 0.85 0.81 0.83 130\n 1 0.80 0.85 0.83 120\n\n accuracy 0.83 250\n macro avg 0.83 0.83 0.83 250\nweighted avg 0.83 0.83 0.83 250\n\n" + } + ], + "execution_count": 16 + }, + { + "id": "2868db31-8b2f-48e0-be98-7bfae983ea68", + "cell_type": "code", + "source": "roc_auc_score(y_test, prediction)", + "metadata": { + "trusted": true + }, + "outputs": [ + { + "execution_count": 17, + "output_type": "execute_result", + "data": { + "text/plain": "0.8288461538461539" + }, + "metadata": {} + } + ], + "execution_count": 17 + }, + { + "id": "75792327-acbf-4cda-bc4b-e1790e892a6b", + "cell_type": "code", + "source": "plt.xlabel(\"first feature\")\nplt.ylabel(\"second feature\")\nplot_2d_separator(knn, X, fill=True)\nplt.scatter(X[:, 0], X[:, 1], c=y, s=70)", + "metadata": { + "trusted": true + }, + "outputs": [ + { + "execution_count": 18, + "output_type": "execute_result", + "data": { + "text/plain": "" + }, + "metadata": {} + }, + { + "output_type": "display_data", + "data": { + "text/plain": "
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" + }, + "metadata": {} + } + ], + "execution_count": 18 + }, + { + "id": "203caf9e-d039-48e6-8178-115a62c39d25", + "cell_type": "code", + "source": "#RS_3", + "metadata": { + "trusted": true + }, + "outputs": [], + "execution_count": 19 + }, + { + "id": "7ecd6f84-210d-429b-b4cd-569439f4dddb", + "cell_type": "code", + "source": "knn = KNeighborsClassifier(n_neighbors=3, metric = 'euclidean')", + "metadata": { + "trusted": true + }, + "outputs": [], + "execution_count": 20 + }, + { + "id": "457e8520-3003-4af3-ba96-ad3363039e00", + "cell_type": "code", + "source": "knn.fit(X_train, y_train)", + "metadata": { + "trusted": true + }, + "outputs": [ + { + "execution_count": 21, + "output_type": "execute_result", + "data": { + "text/plain": "KNeighborsClassifier(metric='euclidean', n_neighbors=3)", + "text/html": "
KNeighborsClassifier(metric='euclidean', n_neighbors=3)
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" + }, + "metadata": {} + } + ], + "execution_count": 21 + }, + { + "id": "f7cd41de-2868-4ad6-bea3-dfb63f142c50", + "cell_type": "code", + "source": "prediction = knn.predict(X_test)", + "metadata": { + "trusted": true + }, + "outputs": [], + "execution_count": 22 + }, + { + "id": "a5f0e649-7c13-4f43-a63f-2a565e1eb6b5", + "cell_type": "code", + "source": "print ('Prediction and test: ')\nprint (prediction)\nprint (y_test)", + "metadata": { + "trusted": true + }, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": "Prediction and test: \n[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\n 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\n 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\n 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\n 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\n 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\n 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]\n[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\n 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\n 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\n 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\n 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\n 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\n 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]\n" + } + ], + "execution_count": 23 + }, + { + "id": "ebe16eca-865c-4fff-90da-3331c8d42956", + "cell_type": "code", + "source": "print ('Confusion matrix: ')\nprint (confusion_matrix(y_test, prediction))", + "metadata": { + "trusted": true + }, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": "Confusion matrix: \n[[104 26]\n [ 6 114]]\n" + } + ], + "execution_count": 24 + }, + { + "id": "ed79892b-31bf-48c5-aa9b-80be354af8bf", + "cell_type": "code", + "source": "print ('Accuracy score: ', accuracy_score(prediction, y_test))", + "metadata": { + "trusted": true + }, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": "Accuracy score: 0.872\n" + } + ], + "execution_count": 25 + }, + { + "id": "af995fbe-a171-4ae5-affb-5a4c9aeab704", + "cell_type": "code", + "source": "print(classification_report(y_test, prediction))", + "metadata": { + "trusted": true + }, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": " precision recall f1-score support\n\n 0 0.95 0.80 0.87 130\n 1 0.81 0.95 0.88 120\n\n accuracy 0.87 250\n macro avg 0.88 0.88 0.87 250\nweighted avg 0.88 0.87 0.87 250\n\n" + } + ], + "execution_count": 26 + }, + { + "id": "d1cabf14-1402-40ac-944c-066e0039be72", + "cell_type": "code", + "source": "roc_auc_score(y_test, prediction)", + "metadata": { + "trusted": true + }, + "outputs": [ + { + "execution_count": 27, + "output_type": "execute_result", + "data": { + "text/plain": "0.875" + }, + "metadata": {} + } + ], + "execution_count": 27 + }, + { + "id": "3deed264-b857-4611-9e3b-ad592f0bbb86", + "cell_type": "code", + "source": "plt.xlabel(\"first feature\")\nplt.ylabel(\"second feature\")\nplot_2d_separator(knn, X, fill=True)\nplt.scatter(X[:, 0], X[:, 1], c=y, s=70)", + "metadata": { + "trusted": true + }, + "outputs": [ + { + "execution_count": 28, + "output_type": "execute_result", + "data": { + "text/plain": "" + }, + "metadata": {} + }, + { + "output_type": "display_data", + "data": { + "text/plain": "
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" + }, + "metadata": {} + } + ], + "execution_count": 28 + }, + { + "id": "c2b6512e-f03f-44f3-83e9-d0cb53ff8b3c", + "cell_type": "code", + "source": "#RS_9", + "metadata": { + "trusted": true + }, + "outputs": [], + "execution_count": 29 + }, + { + "id": "ec803ed1-cd51-4203-a31c-5ecc03ac7080", + "cell_type": "code", + "source": "knn = KNeighborsClassifier(n_neighbors=9, metric = 'euclidean')", + "metadata": { + "trusted": true + }, + "outputs": [], + "execution_count": 30 + }, + { + "id": "74129495-ecd5-4d7a-b3bc-8d9031fb3f54", + "cell_type": "code", + "source": "knn.fit(X_train, y_train)", + "metadata": { + "trusted": true + }, + "outputs": [ + { + "execution_count": 31, + "output_type": "execute_result", + "data": { + "text/plain": "KNeighborsClassifier(metric='euclidean', n_neighbors=9)", + "text/html": "
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.
" + }, + "metadata": {} + } + ], + "execution_count": 31 + }, + { + "id": "96540f64-9ce0-4743-bf8f-6b7186ec93a1", + "cell_type": "code", + "source": "prediction = knn.predict(X_test)", + "metadata": { + "trusted": true + }, + "outputs": [], + "execution_count": 32 + }, + { + "id": "e4adfd8c-07b1-48dd-b257-e38be8aa95a6", + "cell_type": "code", + "source": "print ('Prediction and test: ')\nprint (prediction)\nprint (y_test)", + "metadata": { + "trusted": true + }, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": "Prediction and test: \n[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\n 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\n 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\n 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\n 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\n 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\n 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]\n[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\n 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\n 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\n 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\n 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\n 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\n 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]\n" + } + ], + "execution_count": 33 + }, + { + "id": "f32bdd33-f503-4a83-a615-47e83e6e127f", + "cell_type": "code", + "source": "print ('Confusion matrix: ')\nprint (confusion_matrix(y_test, prediction))", + "metadata": { + "trusted": true + }, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": "Confusion matrix: \n[[100 30]\n [ 3 117]]\n" + } + ], + "execution_count": 34 + }, + { + "id": "9650f1a7-7cc0-40ee-beb4-ea49f8350f20", + "cell_type": "code", + "source": "print ('Accuracy score: ', accuracy_score(prediction, y_test))", + "metadata": { + "trusted": true + }, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": "Accuracy score: 0.868\n" + } + ], + "execution_count": 35 + }, + { + "id": "4150be0e-34b5-4b27-9b97-ea1ed63120a5", + "cell_type": "code", + "source": "print(classification_report(y_test, prediction))", + "metadata": { + "trusted": true + }, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": " precision recall f1-score support\n\n 0 0.97 0.77 0.86 130\n 1 0.80 0.97 0.88 120\n\n accuracy 0.87 250\n macro avg 0.88 0.87 0.87 250\nweighted avg 0.89 0.87 0.87 250\n\n" + } + ], + "execution_count": 36 + }, + { + "id": "6a2a1650-34dd-4c7b-bec1-71ff7f0aec2e", + "cell_type": "code", + "source": "roc_auc_score(y_test, prediction)", + "metadata": { + "trusted": true + }, + "outputs": [ + { + "execution_count": 37, + "output_type": "execute_result", + "data": { + "text/plain": "0.8721153846153846" + }, + "metadata": {} + } + ], + "execution_count": 37 + }, + { + "id": "e247bb52-4218-4a19-b4ed-b2a24ee92f1d", + "cell_type": "code", + "source": "plt.xlabel(\"first feature\")\nplt.ylabel(\"second feature\")\nplot_2d_separator(knn, X, fill=True)\nplt.scatter(X[:, 0], X[:, 1], c=y, s=70)", + "metadata": { + "trusted": true + }, + "outputs": [ + { + "execution_count": 38, + "output_type": "execute_result", + "data": { + "text/plain": "" + }, + "metadata": {} + }, + { + "output_type": "display_data", + "data": { + "text/plain": "
", + "image/png": 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" + }, + "metadata": {} + } + ], + "execution_count": 38 + }, + { + "id": "57a3e07d-6e27-4d19-82e3-6c2b0da1ecce", + "cell_type": "code", + "source": "#GaussianNB", + "metadata": { + "trusted": true + }, + "outputs": [], + "execution_count": 39 + }, + { + "id": "dacec649-0da0-4248-8b69-9f1de0865df8", + "cell_type": "code", + "source": "from sklearn.naive_bayes import GaussianNB", + "metadata": { + "trusted": true + }, + "outputs": [], + "execution_count": 40 + }, + { + "id": "e89f0c72-e8c7-49bc-a687-aba3df966cdc", + "cell_type": "code", + "source": "gnb=GaussianNB()", + "metadata": { + "trusted": true + }, + "outputs": [], + "execution_count": 41 + }, + { + "id": "6c3c9854-442c-420e-b7f5-b105958dd5ea", + "cell_type": "code", + "source": "gnb.fit(X_train, y_train)", + "metadata": { + "trusted": true + }, + "outputs": [ + { + "execution_count": 42, + "output_type": "execute_result", + "data": { + "text/plain": "GaussianNB()", + "text/html": "
GaussianNB()
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" + }, + "metadata": {} + } + ], + "execution_count": 42 + }, + { + "id": "f379197e-5c30-436d-a6a7-5f2802d7cc21", + "cell_type": "code", + "source": "prediction = gnb.predict(X_test)", + "metadata": { + "trusted": true + }, + "outputs": [], + "execution_count": 43 + }, + { + "id": "c6c5da50-4d33-44ad-973f-af05016e1e15", + "cell_type": "code", + "source": "print ('Prediction and test: ')\nprint (prediction)\nprint (y_test)", + "metadata": { + "trusted": true + }, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": "Prediction and test: \n[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\n 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\n 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\n 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\n 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\n 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\n 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]\n[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\n 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\n 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\n 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\n 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\n 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\n 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]\n" + } + ], + "execution_count": 44 + }, + { + "id": "2bb2cbab-0358-49b5-b1ad-7e5bb957bbde", + "cell_type": "code", + "source": "print ('Confusion matrix: ')\nprint (confusion_matrix(y_test, prediction))", + "metadata": { + "trusted": true + }, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": "Confusion matrix: \n[[107 23]\n [ 1 119]]\n" + } + ], + "execution_count": 45 + }, + { + "id": "be8e806a-5a07-4119-a477-849b7c71344c", + "cell_type": "code", + "source": "print ('Accuracy score: ', accuracy_score(prediction, y_test))", + "metadata": { + "trusted": true + }, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": "Accuracy score: 0.904\n" + } + ], + "execution_count": 46 + }, + { + "id": "abeb2561-cfca-4b7f-a6e5-8da720e0a535", + "cell_type": "code", + "source": "print(classification_report(y_test, prediction))", + "metadata": { + "trusted": true + }, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": " precision recall f1-score support\n\n 0 0.99 0.82 0.90 130\n 1 0.84 0.99 0.91 120\n\n accuracy 0.90 250\n macro avg 0.91 0.91 0.90 250\nweighted avg 0.92 0.90 0.90 250\n\n" + } + ], + "execution_count": 47 + }, + { + "id": "f12f2dbb-ed28-4c5a-87d2-7734c2c1e68c", + "cell_type": "code", + "source": "roc_auc_score(y_test, prediction)", + "metadata": { + "trusted": true + }, + "outputs": [ + { + "execution_count": 48, + "output_type": "execute_result", + "data": { + "text/plain": "0.9073717948717948" + }, + "metadata": {} + } + ], + "execution_count": 48 + }, + { + "id": "9cf4ded2-c46d-423a-8f61-0f8b4d4d8bfe", + "cell_type": "code", + "source": "plt.xlabel(\"first feature\")\nplt.ylabel(\"second feature\")\nplot_2d_separator(gnb, X, fill=True)\nplt.scatter(X[:, 0], X[:, 1], c=y, s=70)", + "metadata": { + "trusted": true + }, + "outputs": [ + { + "execution_count": 49, + "output_type": "execute_result", + "data": { + "text/plain": "" + }, + "metadata": {} + }, + { + "output_type": "display_data", + "data": { + "text/plain": "
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" + }, + "metadata": {} + } + ], + "execution_count": 49 + }, + { + "id": "d786fb40-89ce-4b1e-a3dd-1160c1697dbb", + "cell_type": "code", + "source": "#RandFor-5", + "metadata": { + "trusted": true + }, + "outputs": [], + "execution_count": 50 + }, + { + "id": "95df0e84-0a64-40bc-8908-19a886e4f7e9", + "cell_type": "code", + "source": "from sklearn.ensemble import RandomForestClassifier", + "metadata": { + "trusted": true + }, + "outputs": [], + "execution_count": 51 + }, + { + "id": "a0964f55-b395-45b7-841d-98070149912f", + "cell_type": "code", + "source": "rf=RandomForestClassifier(n_estimators=5,random_state=42)", + "metadata": { + "trusted": true + }, + "outputs": [], + "execution_count": 52 + }, + { + "id": "7c7454a2-4e5d-40db-9423-fba594f62ae4", + "cell_type": "code", + "source": "rf.fit(X_train, y_train)", + "metadata": { + "trusted": true + }, + "outputs": [ + { + "execution_count": 53, + "output_type": "execute_result", + "data": { + "text/plain": "RandomForestClassifier(n_estimators=5, random_state=42)", + "text/html": "
RandomForestClassifier(n_estimators=5, random_state=42)
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" + }, + "metadata": {} + } + ], + "execution_count": 53 + }, + { + "id": "a8867b79-c126-4364-b7f5-d6f7b742d04e", + "cell_type": "code", + "source": "prediction = rf.predict(X_test)", + "metadata": { + "trusted": true + }, + "outputs": [], + "execution_count": 54 + }, + { + "id": "4a572642-e40b-4680-ae0f-77198bf1436e", + "cell_type": "code", + "source": "print ('Prediction and test: ')\nprint (prediction)\nprint (y_test)", + "metadata": { + "trusted": true + }, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": "Prediction and test: \n[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\n 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\n 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\n 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\n 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\n 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\n 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]\n[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\n 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\n 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\n 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\n 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\n 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\n 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]\n" + } + ], + "execution_count": 55 + }, + { + "id": "c9295ec0-b569-497d-963d-2b46cf943700", + "cell_type": "code", + "source": "print ('Confusion matrix: ')\nprint (confusion_matrix(y_test, prediction))", + "metadata": { + "trusted": true + }, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": "Confusion matrix: \n[[107 23]\n [ 11 109]]\n" + } + ], + "execution_count": 56 + }, + { + "id": "b873247b-bdbc-4047-9cf6-656f3d8740fd", + "cell_type": "code", + "source": "print ('Accuracy score: ', accuracy_score(prediction, y_test))", + "metadata": { + "trusted": true + }, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": "Accuracy score: 0.864\n" + } + ], + "execution_count": 57 + }, + { + "id": "d523786b-d691-4307-968b-6c0bf2c9ce64", + "cell_type": "code", + "source": "print(classification_report(y_test, prediction))", + "metadata": { + "trusted": true + }, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": " precision recall f1-score support\n\n 0 0.91 0.82 0.86 130\n 1 0.83 0.91 0.87 120\n\n accuracy 0.86 250\n macro avg 0.87 0.87 0.86 250\nweighted avg 0.87 0.86 0.86 250\n\n" + } + ], + "execution_count": 58 + }, + { + "id": "76c68c90-8e61-4de1-921b-66747ff5d0f1", + "cell_type": "code", + "source": "roc_auc_score(y_test, prediction)", + "metadata": { + "trusted": true + }, + "outputs": [ + { + "execution_count": 59, + "output_type": "execute_result", + "data": { + "text/plain": "0.8657051282051281" + }, + "metadata": {} + } + ], + "execution_count": 59 + }, + { + "id": "57adb09c-c617-46c8-9072-b3e3f081d35e", + "cell_type": "code", + "source": "plt.xlabel(\"first feature\")\nplt.ylabel(\"second feature\")\nplot_2d_separator(rf, X, fill=True)\nplt.scatter(X[:, 0], X[:, 1], c=y, s=70)", + "metadata": { + "trusted": true + }, + "outputs": [ + { + "execution_count": 60, + "output_type": "execute_result", + "data": { + "text/plain": "" + }, + "metadata": {} + }, + { + "output_type": "display_data", + "data": { + "text/plain": "
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" + }, + "metadata": {} + } + ], + "execution_count": 60 + }, + { + "id": "b1c17709-9327-4a6b-9e33-0bf8d79e6ccb", + "cell_type": "code", + "source": "#RandFor-15", + "metadata": { + "trusted": true + }, + "outputs": [], + "execution_count": 61 + }, + { + "id": "82bdfda2-5a8d-4ef3-8436-0f624a93c005", + "cell_type": "code", + "source": "rf=RandomForestClassifier(n_estimators=15,random_state=42)", + "metadata": { + "trusted": true + }, + "outputs": [], + "execution_count": 62 + }, + { + "id": "ee021415-871c-49d8-92d7-c22aff8d3f80", + "cell_type": "code", + "source": "rf.fit(X_train, y_train)", + "metadata": { + "trusted": true + }, + "outputs": [ + { + "execution_count": 63, + "output_type": "execute_result", + "data": { + "text/plain": "RandomForestClassifier(n_estimators=15, random_state=42)", + "text/html": "
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.
" + }, + "metadata": {} + } + ], + "execution_count": 63 + }, + { + "id": "f4fe370a-b10a-4ed4-b0f8-272e632c612e", + "cell_type": "code", + "source": "prediction = rf.predict(X_test)", + "metadata": { + "trusted": true + }, + "outputs": [], + "execution_count": 64 + }, + { + "id": "e3ded4cd-045c-4660-ad99-287add294b0d", + "cell_type": "code", + "source": "print ('Prediction and test: ')\nprint (prediction)\nprint (y_test)", + "metadata": { + "trusted": true + }, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": "Prediction and test: \n[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\n 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\n 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\n 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\n 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\n 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\n 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]\n[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\n 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\n 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\n 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\n 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\n 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\n 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]\n" + } + ], + "execution_count": 65 + }, + { + "id": "b516f3a3-6695-44cf-8008-519a91b51fbe", + "cell_type": "code", + "source": "print ('Confusion matrix: ')\nprint (confusion_matrix(y_test, prediction))", + "metadata": { + "trusted": true + }, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": "Confusion matrix: \n[[109 21]\n [ 8 112]]\n" + } + ], + "execution_count": 66 + }, + { + "id": "b205cc78-d821-4fb9-a97d-3fb903dc3df0", + "cell_type": "code", + "source": "print ('Accuracy score: ', accuracy_score(prediction, y_test))", + "metadata": { + "trusted": true + }, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": "Accuracy score: 0.884\n" + } + ], + "execution_count": 67 + }, + { + "id": "0ae981de-5559-4ea3-b1e4-f1564f9b9edd", + "cell_type": "code", + "source": "print(classification_report(y_test, prediction))", + "metadata": { + "trusted": true + }, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": " precision recall f1-score support\n\n 0 0.93 0.84 0.88 130\n 1 0.84 0.93 0.89 120\n\n accuracy 0.88 250\n macro avg 0.89 0.89 0.88 250\nweighted avg 0.89 0.88 0.88 250\n\n" + } + ], + "execution_count": 68 + }, + { + "id": "ecee820f-c51d-41ad-a67b-4aaa4ba48881", + "cell_type": "code", + "source": "roc_auc_score(y_test, prediction)", + "metadata": { + "trusted": true + }, + "outputs": [ + { + "execution_count": 69, + "output_type": "execute_result", + "data": { + "text/plain": "0.885897435897436" + }, + "metadata": {} + } + ], + "execution_count": 69 + }, + { + "id": "657273c4-fbbc-4739-aaf1-cce86411b8bb", + "cell_type": "code", + "source": "plt.xlabel(\"first feature\")\nplt.ylabel(\"second feature\")\nplot_2d_separator(rf, X, fill=True)\nplt.scatter(X[:, 0], X[:, 1], c=y, s=70)", + "metadata": { + "trusted": true + }, + "outputs": [ + { + "execution_count": 70, + "output_type": "execute_result", + "data": { + "text/plain": "" + }, + "metadata": {} + }, + { + "output_type": "display_data", + "data": { + "text/plain": "
", + "image/png": 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" + }, + "metadata": {} + } + ], + "execution_count": 70 + }, + { + "id": "b5d0bf24-49c9-4a33-8760-bc086f9e1bf9", + "cell_type": "code", + "source": "#RandFor-50", + "metadata": { + "trusted": true + }, + "outputs": [], + "execution_count": 71 + }, + { + "id": "d80adbec-43e1-4c6c-8856-36a3c3f51a85", + "cell_type": "code", + "source": "rf=RandomForestClassifier(n_estimators=50,random_state=42)", + "metadata": { + "trusted": true + }, + "outputs": [], + "execution_count": 72 + }, + { + "id": "bd457cf0-47c7-4a48-8e6a-1e56877bd120", + "cell_type": "code", + "source": "rf.fit(X_train, y_train)", + "metadata": { + "trusted": true + }, + "outputs": [ + { + "execution_count": 73, + "output_type": "execute_result", + "data": { + "text/plain": "RandomForestClassifier(n_estimators=50, random_state=42)", + "text/html": "
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.
" + }, + "metadata": {} + } + ], + "execution_count": 73 + }, + { + "id": "6d27f0d0-4515-4ab7-9d02-e6189448918d", + "cell_type": "code", + "source": "prediction = rf.predict(X_test)", + "metadata": { + "trusted": true + }, + "outputs": [], + "execution_count": 74 + }, + { + "id": "6c19ec0b-51e4-49bc-8540-3b92465e4f61", + "cell_type": "code", + "source": "print ('Prediction and test: ')\nprint (prediction)\nprint (y_test)", + "metadata": { + "trusted": true + }, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": "Prediction and test: \n[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\n 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\n 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\n 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\n 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\n 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\n 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]\n[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\n 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\n 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\n 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\n 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\n 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\n 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]\n" + } + ], + "execution_count": 75 + }, + { + "id": "e466dddd-067c-406f-bdb8-56c43e3e24db", + "cell_type": "code", + "source": "print ('Confusion matrix: ')\nprint (confusion_matrix(y_test, prediction))", + "metadata": { + "trusted": true + }, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": "Confusion matrix: \n[[110 20]\n [ 9 111]]\n" + } + ], + "execution_count": 76 + }, + { + "id": "2aaa9a1e-097a-452d-aea2-e21fc436e832", + "cell_type": "code", + "source": "print ('Accuracy score: ', accuracy_score(prediction, y_test))", + "metadata": { + "trusted": true + }, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": "Accuracy score: 0.884\n" + } + ], + "execution_count": 77 + }, + { + "id": "167100bd-2756-487a-933a-8e41a4c08fb5", + "cell_type": "code", + "source": "print(classification_report(y_test, prediction))", + "metadata": { + "trusted": true + }, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": " precision recall f1-score support\n\n 0 0.92 0.85 0.88 130\n 1 0.85 0.93 0.88 120\n\n accuracy 0.88 250\n macro avg 0.89 0.89 0.88 250\nweighted avg 0.89 0.88 0.88 250\n\n" + } + ], + "execution_count": 78 + }, + { + "id": "00c100db-a9ba-4304-bf23-23106f296d68", + "cell_type": "code", + "source": "roc_auc_score(y_test, prediction)", + "metadata": { + "trusted": true + }, + "outputs": [ + { + "execution_count": 79, + "output_type": "execute_result", + "data": { + "text/plain": "0.885576923076923" + }, + "metadata": {} + } + ], + "execution_count": 79 + }, + { + "id": "4dca6ea1-f7d5-4197-9c5e-b1e9b4ef02b1", + "cell_type": "code", + "source": "plt.xlabel(\"first feature\")\nplt.ylabel(\"second feature\")\nplot_2d_separator(rf, X, fill=True)\nplt.scatter(X[:, 0], X[:, 1], c=y, s=70)", + "metadata": { + "trusted": true + }, + "outputs": [ + { + "execution_count": 80, + "output_type": "execute_result", + "data": { + "text/plain": "" + }, + "metadata": {} + }, + { + "output_type": "display_data", + "data": { + "text/plain": "
", + "image/png": 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