A simple graphical frontend for Libsvm mainly intended for didactic purposes. You can create data points by point and click and visualize the decision region induced by different

Sample usage of Nearest Neighbors classification. It will plot the decision boundaries for each class.

This example demonstrates the behavior of Gaussian mixture models fit on data that was not sampled from a mixture of Gaussian random variables. The dataset

An example using a one-class SVM for novelty detection.

Demonstrates an active learning technique to learn handwritten digits using label propagation. We start by training a label propagation model

Computes Lasso Path along the regularization parameter using the LARS algorithm on the diabetes dataset. Each color represents a different feature of the coefficient vector

Using orthogonal matching pursuit for recovering a sparse signal from a noisy measurement encoded with a dictionary print(__doc__)

In this example we see how to robustly fit a linear model to faulty data using the RANSAC algorithm.

A tutorial exercise using Cross-validation with an SVM on the Digits dataset. This exercise is used in the

The PCA does an unsupervised dimensionality reduction, while the logistic regression does the prediction. We use a GridSearchCV to