documention and examples for mlpy
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.
This package provides user documentation for mlpy in various formats (HTML, PDF).
Related packages: python-mlpy, python-mlpy-lib
Version control system available: Browse sources
| Distribution | Base version | Our version | Architectures |
|---|---|---|---|
| Debian GNU/Linux 6.0 (squeeze) | 2.2.0~dfsg1-2 | 2.2.0~dfsg1-1~squeeze.nd1 | i386, amd64, sparc |
| Debian GNU/Linux 7.0 (wheezy) | 2.2.0~dfsg1-2 | ||
| Debian GNU/Linux 8.0 (jessie) | 2.2.0~dfsg1-2.1 | ||
| Debian testing (stretch) | 2.2.0~dfsg1-2.1 | ||
| Debian unstable (sid) | 2.2.0~dfsg1-2.1 | ||
| Ubuntu 10.04 LTS “Lucid Lynx” (lucid) | 2.1.0~dfsg1-2 | 2.2.0~dfsg1-1~lucid.nd1 | i386, amd64 |
| Ubuntu 12.04 LTS “Precise Pangolin” (precise) | 2.2.0~dfsg1-2build2 | ||
| Ubuntu 14.04 “Trusty Tahr” (trusty) | 2.2.0~dfsg1-2.1 | ||
| Ubuntu 14.10 “Utopic Unicorn” (utopic) | 2.2.0~dfsg1-2.1 | ||
| Ubuntu 15.04 “Vivid Vervet” (vivid) | 2.2.0~dfsg1-2.1 |