def test_with_defaults(self):
trainable = VotingClassifier(
estimators=[("lr",
LogisticRegression()), ("dt",
DecisionTreeClassifier())])
trained = trainable.fit(self.train_X, self.train_y)
_ = trained.predict(self.test_X)
def test_with_lale_classifiers(self):
clf = VotingClassifier(
estimators=[("knn",
KNeighborsClassifier()), ("lr",
LogisticRegression())])
trained = clf.fit(self.X_train, self.y_train)
trained.predict(self.X_test)
def test_estimators(self):
trainable = VotingClassifier(estimators=[(
'lr',
LogisticRegression()), ('dt',
DecisionTreeClassifier()), ('na', None)])
trained = trainable.fit(self.train_X, self.train_y)
predicted = trained.predict(self.test_X)
def test_estimators(self):
trainable = VotingClassifier(estimators=[
("lr", LogisticRegression()),
("dt", DecisionTreeClassifier()),
("na", None),
])
trained = trainable.fit(self.train_X, self.train_y)
predicted = trained.predict(self.test_X)
def test_with_lale_pipeline(self):
from lale.lib.sklearn import VotingClassifier
clf = VotingClassifier(estimators=[
("knn", KNeighborsClassifier()),
("pca_lr", PCA() >> LogisticRegression()),
])
trained = clf.fit(self.X_train, self.y_train)
trained.predict(self.X_test)