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- Description:
Machine Learning PY (mlpy) is a high-performance Python package for predictive modeling. It makes extensive use of numpy (http://scipy.org) to provide fast N-dimensional array manipulation and easy integration of C code. mlpy provides high level procedures that support, with few lines of code, the design of rich Data Analysis Protocols (DAPs) for preprocessing, clustering, predictive classification and feature selection. Methods are available for feature weighting and ranking, data resampling, error evaluation and experiment landscaping. The package includes tools to measure stability in sets of ranked feature lists.
mlpy is a project of Predictive Models for Biological and Environmental Data Analysis (MPBA) Research Unit mpba.fbk.eu at Fondazione Bruno Kessler.
mlpy is cofinanced by Associazione Italiana per la Ricerca sul Cancro (AIRC).
- Changes to previous version:
New features:
- HCluster: sample <-> feature in input data x. Groups are now in 0, ..., N-1
- k-medoids added
- minkowski distance added
- Documentation improved
Bug fixes:
- canberraq tool fixed
- Svm(): MatrixKernelGaussian() for Svm.weights() speeded up
- BibTeX Entry: Download
- Supported Operating Systems: Linux, Macosx, Windows, Unix, Freebsd
- Data Formats: None
- Tags: Svm, Classification, Clustering, Fda, Feature Weighting, Irelief, Rfe, Feature Ranking, Resampling, Srda, Nn, Dwt, Pda, Nips2008, Dlda, Wavelet, Imputing, Dtw, Kmedoids
- Archive: download here
Comments
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- jacob Yang (on April 30, 2010, 14:24:11)
- when the program is running, there is no output. I don't know when it will be finish.
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- Michele Filosi (on December 13, 2011, 10:04:04)
- Very useful and well implemented!
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