sklearn.datasets.load_diabetes(return_X_y=False)

class sklearn.feature_selection.RFECV(estimator, step=1, cv=None, scoring=None, verbose=0, n_jobs=1)

class sklearn.svm.LinearSVC(penalty='l2', loss='squared_hinge', dual=True, tol=0.0001, C=1.0, multi_class='ovr', fit_intercept=True, intercept_scaling=1

sklearn.utils.check_random_state(seed)

class sklearn.cluster.MiniBatchKMeans(n_clusters=8, init='k-means++', max_iter=100, batch_size=100, verbose=0, compute_labels=True

sklearn.feature_selection.f_regression(X, y, center=True)

class sklearn.ensemble.BaggingClassifier(base_estimator=None, n_estimators=10, max_samples=1.0, max_features=1.0, bootstrap=True

class sklearn.cluster.AffinityPropagation(damping=0.5, max_iter=200, convergence_iter=15, copy=True, preference=None, affinity='euclidean'

class sklearn.decomposition.LatentDirichletAllocation(n_topics=10, doc_topic_prior=None, topic_word_prior=None, learning_method=None

class sklearn.neighbors.KNeighborsRegressor(n_neighbors=5, weights='uniform', algorithm='auto', leaf_size=30, p=2, metric='minkowski'