Plot decision function of a weighted dataset, where the size of points is proportional to its weight. The sample weighting rescales the C parameter, which means

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

This example compares 2 dimensionality reduction strategies: univariate feature selection with Anova feature

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

A plot that compares the various convex loss functions supported by

This dataset is made up of 1797 8x8 images. Each image, like the one shown below, is of a hand-written digit. In order to utilize an 8x8 figure like this, we?d have to first

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

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

Out-of-bag (OOB) estimates can be a useful heuristic to estimate the ?optimal? number of boosting iterations. OOB estimates are almost identical to cross-validation

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