An example showing univariate feature selection. Noisy (non informative) features are added to the iris data and univariate feature selection is applied

Plot decision surface of multi-class SGD on iris dataset. The hyperplanes corresponding to the three one-versus-all (OVA) classifiers are represented

Due to the few points in each dimension and the straight line that linear regression uses to follow these points as well as it can, noise

Plot the class probabilities of the first sample in a toy dataset predicted by three different classifiers and averaged by the

Example of Receiver Operating Characteristic (ROC) metric to evaluate classifier output quality. ROC curves typically feature true positive rate

In this example we compare the various initialization strategies for K-means in terms of runtime and quality of the results.

This example shows how kernel density estimation (KDE), a powerful non-parametric density estimation technique, can be used to learn a generative model for a dataset

Illustration of the effect of different regularization strategies for Gradient Boosting. The example is taken from Hastie et al 2009. The loss function

This example uses the

This example demonstrates how to generate a dataset and bicluster it using the Spectral Co-Clustering algorithm. The dataset is generated