Computes Lasso Path along the regularization parameter using the LARS algorithm on the diabetes dataset. Each color represents a different feature of the coefficient vector

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

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

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

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 example uses a large dataset of faces to learn a set of 20 x 20 images patches that constitute faces. From the programming standpoint

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

In this example we see how to robustly fit a linear model to faulty data using the RANSAC algorithm.

The PCA does an unsupervised dimensionality reduction, while the logistic regression does the prediction. We use a GridSearchCV to

Plot the contours of the three penalties. All of the above are supported by sklearn.linear_model.stochastic_gradient.