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])
