def test_clone_with_scikit1(self): lr = LogisticRegression() lr.get_params() from sklearn.base import clone lr_clone = clone(lr) self.assertNotEqual(lr, lr_clone) self.assertNotEqual(lr._impl, lr_clone._impl) iris = load_iris() trained_lr = lr.fit(iris.data, iris.target) _ = trained_lr.predict(iris.data) cloned_trained_lr = clone(trained_lr) self.assertNotEqual(trained_lr._impl, cloned_trained_lr._impl)
def test_clone_with_scikit1(self): lr = LogisticRegression() lr.get_params() from sklearn.base import clone lr_clone = clone(lr) self.assertNotEqual(lr, lr_clone) self.assertNotEqual(lr._impl, lr_clone._impl) iris = sklearn.datasets.load_iris() trained_lr = lr.fit(iris.data, iris.target) predicted = trained_lr.predict(iris.data) cloned_trained_lr = clone(trained_lr) self.assertNotEqual(trained_lr._impl, cloned_trained_lr._impl) predicted_clone = cloned_trained_lr.predict(iris.data) for i in range(len(iris.target)): self.assertEqual(predicted[i], predicted_clone[i])