class sklearn.gaussian_process.kernels.Sum(k1, k2)

sklearn.metrics.pairwise_distances_argmin(X, Y, axis=1, metric='euclidean', batch_size=500, metric_kwargs=None)

An illustration of various embeddings on the digits dataset. The RandomTreesEmbedding, from the

Finds core samples of high density and expands clusters from them. print(__doc__) import numpy as np from

class sklearn.preprocessing.FunctionTransformer(func=None, inverse_func=None, validate=True, accept_sparse=False, pass_y=False

This example illustrates GPC on XOR data. Compared are a stationary, isotropic kernel (RBF) and a non-stationary kernel

An example using IsolationForest for anomaly detection. The IsolationForest ?isolates? observations by randomly selecting a feature and then randomly selecting

Example of LabelPropagation learning a complex internal structure to demonstrate ?manifold learning?. The outer circle should be labeled ?red

class sklearn.model_selection.GroupKFold(n_splits=3)

Fit regression model with Bayesian Ridge Regression. See