def score(self, X_test, y_test):
y_predict = self.predict(X_test)
return r2_score(y_test, y_predict)
train_X, train_y = get_train_data()
test_X, test_y = get_test_data()
from sklearn.linear_model import LinearRegression
clf = LinearRegression()
clf.fit(train_X, train_y)
print(clf.coef_)
print('sklearn:', clf.score(test_X, test_y))
clf = LinearRegressionGD()
w1 = clf.adagrad(train_X, train_y)
y_pred = clf.predict(test_X)
print(clf.score(test_X, test_y))
clf = LinearRegressionGD()
w1 = clf.BGD(train_X, train_y)
y_pred = clf.predict(test_X)
print(clf.score(test_X, test_y))
clf = LinearRegressionGD()
w1 = clf.SGD(train_X, train_y)
y_pred = clf.predict(test_X)
print(clf.score(test_X, test_y))
