from sklearn.linear_model import SGDClassifier from sklearn.preprocessing import StandardScaler X = [[0., 0.], [1., 1.]] y = [0, 1] clf = SGDClassifier(loss="hinge", penalty="l2") print clf.fit(X, y) print clf.predict([[2., 2.]]) print clf.coef_ print clf.intercept_ print clf.decision_function([[2., 2.]]) clf = SGDClassifier(loss='log').fit(X, y) print clf.predict_ probab([[1., 1.]]) scaler = StandardScaler() scaler.fot(X_train) X_train = scaler.transform(X_train) X_test = scaler.transform(X_test)
