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:

• New function span_pd(). three_points_pd() deprecated.
• New Dtw class (dtw() has been removed):
  • Naive and Derivative DTW
  • Symmetric, Asymmetric, Quasi-Symmetric implementation with Slope Constraint Condition P=0
  • Sakoe-Chiba window condition option
  • Linear space-complexity implementation option
  • (0, 0) boundary condition option
• canberra() - canberraq(): new option 'dist' returns partial distances
• canberra - canberraq: partial distances to file(s) added
• Documentation improved

Bug fixes:

• Derivative DTW algorithm fixed
• knn_imputing() inf2 bug fixed

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

Archive: download here

Comments

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.

Michele Filosi (on December 13, 2011, 10:04:04)

Very useful and well implemented!

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