This is an example of applying Non-negative Matrix Factorization and Latent Dirichlet Allocation on a

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

This example demonstrates the problems of underfitting and overfitting and how we can use linear regression with polynomial features to approximate nonlinear functions

An example showing how the scikit-learn can be used to recognize images of hand-written digits. This example is commented in the

Simple usage of Support Vector Machines to classify a sample. It will plot the decision surface and the support vectors.

Making sure that each Feature has approximately the same scale can be a crucial preprocessing step. However, when data contains outliers,

This example is based on Figure 10.2 from Hastie et al 2009 [1] and illustrates the difference in performance between the discrete SAMME [2] boosting algorithm

Illustration of how the performance of an estimator on unseen data (test data) is not the same as the performance on training data. As the regularization increases

This is an example showing how scikit-learn can be used for classification using an out-of-core approach: learning from data that doesn?t fit into

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