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

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

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

Compares FeatureHasher and DictVectorizer by using both to vectorize text documents. The example demonstrates syntax and speed only; it doesn

A plot that compares the various convex loss functions supported by

This example plots the ellipsoids obtained from a toy dataset (mixture of three Gaussians) fitted by the Baye

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 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

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

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