Useful Snippets

This page points to useful snippets of code (gists in github-speak) that implement features related to scikit-learn but that might not be suitable for inclusion (yet):

• Multi-Layer-Perceptron (neural network) classifier, trained with SGD. Could serve as a basis for a Cython-Version for later inclusion.
• Generating data with non-parametric Gaussian mixture models. Useful if you need "random" data that should have non-trivial structure.
• Adaptive Lasso (should be added to linear_model)
• Non-Negative Garotte (should be added to linear_model)
• Kernel SGD
• Fuzzy K-means and K-medians
• Fast svmlight / libsvm file loader

If you think that some of these snippets are very useful, we encourage you to work on them so that they can be included in scikit-learn. This entails writing tests, documentation, checking for low hanging performance optimization, and making sure that they follow well the scikit-learn API. See the contributing guide.