def test_with_hyperopt(self):
from lale.lib.lale import Hyperopt
from lale.lib.sklearn import VotingClassifier
clf = VotingClassifier(
estimators=[("knn", KNeighborsClassifier()), ("lr", LogisticRegression())]
)
_ = clf.auto_configure(self.X_train, self.y_train, Hyperopt, max_evals=1)
def test_with_hyperopt(self):
planned = VotingClassifier(
estimators=[("lr", LogisticRegression), ("dt", DecisionTreeClassifier)]
)
trained = planned.auto_configure(
self.train_X, self.train_y, optimizer=Hyperopt, cv=3, max_evals=3
)
_ = trained.predict(self.test_X)
def test_with_gridsearch(self):
from sklearn.metrics import accuracy_score, make_scorer
from lale.lib.lale import GridSearchCV
from lale.lib.sklearn import VotingClassifier
clf = VotingClassifier(
estimators=[("knn", KNeighborsClassifier()), ("rc", RidgeClassifier())],
voting="hard",
)
_ = clf.auto_configure(
self.X_train,
self.y_train,
GridSearchCV,
lale_num_samples=1,
lale_num_grids=1,
cv=2,
scoring=make_scorer(accuracy_score),
)