class sklearn.linear_model.OrthogonalMatchingPursuit(n_nonzero_coefs=None, tol=None, fit_intercept=True, normalize=True

sklearn.manifold.spectral_embedding(adjacency, n_components=8, eigen_solver=None, random_state=None, eigen_tol=0.0, norm_laplacian=True

sklearn.metrics.calinski_harabaz_score(X, labels)

class sklearn.ensemble.GradientBoostingClassifier(loss='deviance', learning_rate=0.1, n_estimators=100, subsample=1.0,

class sklearn.ensemble.ExtraTreesClassifier(n_estimators=10, criterion='gini', max_depth=None, min_samples_split=2, min_samples_leaf=1

class sklearn.gaussian_process.kernels.PairwiseKernel(gamma=1.0, gamma_bounds=(1e-05, 100000.0), metric='linear',

sklearn.cluster.ward_tree(X, connectivity=None, n_clusters=None, return_distance=False)

sklearn.datasets.make_friedman2(n_samples=100, noise=0.0, random_state=None)

class sklearn.neighbors.LSHForest(n_estimators=10, radius=1.0, n_candidates=50, n_neighbors=5, min_hash_match=4, radius_cutoff_ratio=0

class sklearn.preprocessing.PolynomialFeatures(degree=2, interaction_only=False, include_bias=True)