Milk is a machine learning toolkit in Python. Its focus is on supervised classification with several classifiers available: SVMs, k-NN, random forests, decision trees. It also performs feature selection. These classifiers can be combined in many ways to form different classification systems. For unsupervised learning, milk supports k-means clustering and affinity propagation.

Features

• SVMs. Using the libsvm solver with a pythonesque wrapper around it.
• LASSO
• K-means using as little memory as possible. It can cluster millions of instances efficiently.
• Random forests
• Self organising maps
• Stepwise Discriminant Analysis for feature selection.
• Non-negative matrix factorisation
• Affinity propagation

Information

• Website: http://www.luispedro.org/software/milk/
• GitHub: https://github.com/luispedro/milk
• Documentation: http://packages.python.org/milk/
• Community: http://groups.google.com/group/milk-users