def test_with_observed_gridsearch(self): from lale.lib.sklearn import VotingClassifier from lale.lib.lale import GridSearchCV from lale.lib.lale import Observing from lale.lib.lale.observing import LoggingObserver from sklearn.metrics import accuracy_score, make_scorer clf = VotingClassifier(estimators=[('knn', KNeighborsClassifier()), ('rc', RidgeClassifier())], voting='hard') trained = 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), observer=LoggingObserver)
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), )
def test_ridge_classifier_1(self): from lale.lib.sklearn import RidgeClassifier reg = RidgeClassifier(solver='svd', max_iter=10) reg.fit(self.X_train, self.y_train)
def test_ridge_classifier(self): from lale.lib.sklearn import RidgeClassifier reg = RidgeClassifier(fit_intercept=False, normalize=True) reg.fit(self.X_train, self.y_train)
def test_ridge_classifier_1(self): reg = RidgeClassifier(solver="svd", max_iter=10) reg.fit(self.X_train, self.y_train)
def test_ridge_classifier(self): reg = RidgeClassifier(fit_intercept=False, normalize=True) reg.fit(self.X_train, self.y_train)