This examples shows the use of forests of trees to evaluate the importance of features on an artificial classification task. The red bars are the feature

RandomTreesEmbedding provides a way to map data to a very high-dimensional, sparse representation, which might be beneficial for classification

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.

Find the optimal separating hyperplane using an SVC for classes that are unbalanced. We first find the separating plane with a plain

This example studies the scalability profile of approximate 10-neighbors queries using the LSHForest with n_estimators=20 and

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

Using the GraphLasso estimator to learn a covariance and sparse precision from a small number of samples. To estimate a probabilistic model (e.g

Incremental principal component analysis (IPCA) is typically used as a replacement for principal component analysis (PCA) when the dataset to be decomposed is too large to fit

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