We show that linear_model.Lasso provides the same results for dense and sparse data and that in the case of sparse data the speed is improved.

Plot the density estimation of a mixture of two Gaussians. Data is generated from two Gaussians with different centers and covariance matrices.

Comparison of the sparsity (percentage of zero coefficients) of solutions when L1 and L2 penalty are used for different values of C. We can see

This is an example showing how the scikit-learn can be used to cluster documents by topics using a bag-of-words approach. This example uses a scipy.sparse

Transform your features into a higher dimensional, sparse space. Then train a linear model on these features. First fit an ensemble of

This example shows how to use cross_val_predict to visualize prediction errors.

In many real-world examples, there are many ways to extract features from a dataset. Often it is beneficial to combine several methods to obtain

This example shows that Kernel PCA is able to find a projection of the data that makes data linearly separable.

Plot decision function of a weighted dataset, where the size of points is proportional to its weight.

This illustrates the datasets.make_multilabel_classification dataset generator. Each sample consists of counts of two features (up to