This example shows how quantile regression can be used to create prediction intervals.

Plot the classification probability for different classifiers. We use a 3 class dataset, and we classify it with a Support Vector classifier, L1 and L2 penalized

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

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

In order to test if a classification score is significative a technique in repeating the classification procedure after randomizing

Example of Receiver Operating Characteristic (ROC) metric to evaluate classifier output quality using cross-validation. ROC

The plots display firstly what a K-means algorithm would yield using three clusters. It is then shown what the effect of a bad initialization is on the classification process: