a flexible, fast machine learning library

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  • License: BSD License (BSD)
  • Author: mlpack developers
  • Tags machine learning, data mining, deep learning, optimization
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Project description

mlpack is a fast, flexible machine learning library, written in C++, that aims to provide fast, extensible implementations of cutting-edge machine learning algorithms. mlpack provides these algorithms as standalone Python functions, which wrap the fast C++ implementations of the algorithms.

mlpack's techniques fall into a handful of categories:

  • Classification: logistic regression, perceptrons, random forests, linear SVMs, AdaBoost, etc.

  • Regression: linear regression, least angle regression, etc.

  • Clustering: Gaussian mixture models, k-means, mean shift, DBSCAN, etc.

  • Geometry: k-nearest-neighbor search, max-kernel search, locality sensitive hashing (LSH), etc.

  • Preprocessing: dataset splitting, binarization, scaling, one hot encoding, etc.

  • Misc. / Other: collaborative filtering, density estimation trees, Hidden Markov Models, kernel density estimation (KDE), etc.

  • Transformations: kernel PCA, sparse coding, large margin nearest neighbors, PCA, etc.

For more documentation on each individual function that mlpack provides, see the Python binding documentation.

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