def test_init_fit_predict(self):
import sklearn.datasets
import sklearn.svm
svm = sklearn.svm.SVR(kernel='linear')
rfe = RFE(estimator=svm, n_features_to_select=2)
lr = LogisticRegression()
trainable = rfe >> lr
data = sklearn.datasets.load_iris()
X, y = data.data, data.target
trained = trainable.fit(X, y)
predicted = trained.predict(X)
def test_hyperparam_estimator(self):
lr = LogisticRegression()
linear_reg = LinearRegression()
ada = AdaBoostRegressor(base_estimator=lr)
replaced_ada = ada.replace(lr, linear_reg)
expected_ada = AdaBoostRegressor(base_estimator=linear_reg)
self.assertEqual(replaced_ada.to_json(), expected_ada.to_json())
replaced_ada = ada.replace(LogisticRegression, linear_reg)
expected_ada = AdaBoostRegressor(base_estimator=linear_reg)
self.assertEqual(replaced_ada.to_json(), expected_ada.to_json())
ada_pipeline = PCA >> SimpleImputer >> ada
replaced_pipeline = ada_pipeline.replace(lr, linear_reg)
expected_pipeline = (
PCA >> SimpleImputer >> AdaBoostRegressor(base_estimator=linear_reg)
)
self.assertEqual(replaced_pipeline.to_json(), expected_pipeline.to_json())
ada_choice = PCA | ada
replaced_choice = ada_choice.replace(lr, linear_reg)
expected_choice = PCA | AdaBoostRegressor(base_estimator=linear_reg)
self.assertEqual(replaced_choice.to_json(), expected_choice.to_json())
rfe = RFE(estimator=lr)
replaced_rfe = rfe.replace(lr, linear_reg)
expected_rfe = RFE(estimator=linear_reg)
self.assertEqual(replaced_rfe.to_json(), expected_rfe.to_json())
def test_attrib(self):
import sklearn.datasets
from lale.lib.sklearn import RFE, LogisticRegression
svm = lale.lib.sklearn.SVR(kernel="linear")
rfe = RFE(estimator=svm, n_features_to_select=2)
lr = LogisticRegression()
trainable = rfe >> lr
data = sklearn.datasets.load_iris()
X, y = data.data, data.target
trained = trainable.fit(X, y)
_ = trained.predict(X)
from lale.lib.lale import Hyperopt
opt = Hyperopt(estimator=trainable, max_evals=2, verbose=True)
opt.fit(X, y)
def test_not_operator(self):
with EnableSchemaValidation():
with self.assertRaises(jsonschema.ValidationError):
_ = RFE(estimator='"not an operator"', n_features_to_select=2)