Demonstration of several covariances types for Gaussian mixture models. See

This example is based on Section 5.4.3 of ?Gaussian Processes for Machine Learning? [RW2006]. It illustrates an example of complex kernel

Example builds a swiss roll dataset and runs hierarchical clustering on their position. For more information, see

Plot the decision surface of a decision tree trained on pairs of features of the iris dataset. See

This example employs several unsupervised learning techniques to extract the stock market structure from variations in historical quotes. The quantity

A simple one-dimensional regression example computed in two different ways: A noise-free case

Reference: Brendan J. Frey and Delbert Dueck, ?Clustering by Passing Messages Between Data Points?, Science Feb. 2007

A 1D regression with decision tree. The

This example simulates a multi-label document classification problem. The dataset is generated randomly based on the following process: pick

This example illustrates the effect of the parameters gamma and C of the Radial Basis Function (RBF) kernel SVM. Intuitively, the gamma