Fit regression model with Bayesian Ridge Regression. See

An example showing how different online solvers perform on the hand-written digits dataset.

This example applies to The Olivetti faces dataset different unsupervised matrix decomposition (dimension reduction) methods from

sklearn.datasets.make_spd_matrix(n_dim, random_state=None)

The multi-task lasso allows to fit multiple regression problems jointly enforcing the selected features to be the same across tasks. This example

This example demonstrates how to generate a checkerboard dataset and bicluster it using the Spectral Biclustering algorithm. The data is

Demonstrate how model complexity influences both prediction accuracy and computational performance. The dataset is the Boston Housing dataset (resp. 20 Newsgroups)

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

sklearn.datasets.make_sparse_coded_signal(n_samples, n_components, n_features, n_nonzero_coefs, random_state=None)

class sklearn.manifold.TSNE(n_components=2, perplexity=30.0, early_exaggeration=4.0, learning_rate=1000.0, n_iter=1000, n_iter_without_progress=30