This commit is contained in:
Ctrl-Tim 2023-12-10 15:35:33 +04:00
parent ba4a6f1402
commit fece83fa1a
2 changed files with 84 additions and 37 deletions

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View File

@ -9,12 +9,11 @@
import numpy as np import numpy as np
from sklearn.datasets import make_classification from sklearn.datasets import make_classification
from sklearn.linear_model import LinearRegression, Perceptron, Ridge from sklearn.linear_model import LinearRegression, Perceptron, Ridge
from matplotlib import pyplot as plt
from matplotlib.colors import ListedColormap
from sklearn.model_selection import train_test_split from sklearn.model_selection import train_test_split
from sklearn.metrics import mean_absolute_error, mean_squared_error, accuracy_score, balanced_accuracy_score
from sklearn.pipeline import make_pipeline from sklearn.pipeline import make_pipeline
from sklearn.preprocessing import PolynomialFeatures from sklearn.preprocessing import PolynomialFeatures
from matplotlib import pyplot as plt
from matplotlib.colors import ListedColormap
@ -48,10 +47,7 @@ def my_linear_regression(X_train, X_test, y_train, y_test):
# вывод в консоль # вывод в консоль
print() print()
print('===> Линейная регрессия <===') print('===> Линейная регрессия <===')
print('Оценка точности:') print('Оценка точности: ', lin_reg_model.score(X_train, y_train))
print('MAE:', mean_absolute_error(y_test, y_pred))
print('MSE:', mean_squared_error(y_test, y_pred))
print()
# вывод в график # вывод в график
plt.title('Линейная регрессия') plt.title('Линейная регрессия')
@ -71,10 +67,7 @@ def my_perceptron(X_train, X_test, y_train, y_test):
# вывод в консоль # вывод в консоль
print() print()
print('===> Персептрон <===') print('===> Персептрон <===')
print('Оценка точности:') print('Оценка точности: ', perceptron_model.score(X_train, y_train))
print('По тренировочным данным: ', perceptron_model.score(X_train, y_train))
print('По тестовым данным: ', accuracy_score(y_test, y_pred))
print()
# вывод в график # вывод в график
plt.title('Персептрон') plt.title('Персептрон')
@ -94,10 +87,7 @@ def my_poly_ridge(X_train, X_test, y_train, y_test):
# вывод в консоль # вывод в консоль
print() print()
print('===> Гребневая полиномиальная регрессия <===') print('===> Гребневая полиномиальная регрессия <===')
print('Оценка точности:') print('Оценка точности: ', poly_rige_model.score(X_train, y_train))
print('MAE:', mean_absolute_error(y_test, y_pred))
print('MSE:', mean_squared_error(y_test, y_pred))
print()
# вывод в график # вывод в график
plt.title('Гребневая полиномиальная регрессия') plt.title('Гребневая полиномиальная регрессия')