Author: tille Date: Wed Jun 16 06:50:18 2010 New Revision: 2208 URL: http://svn.debian.org/viewsvn/blends?rev=2208&view=rev
Log: Added Pkg-Description fields to prospective packages (copied from ITP bugs) Modified: projects/science/trunk/debian-science/tasks/machine-learning Modified: projects/science/trunk/debian-science/tasks/machine-learning URL: http://svn.debian.org/viewsvn/blends/projects/science/trunk/debian-science/tasks/machine-learning?rev=2208&view=diff&r1=2208&r2=2207&p1=projects/science/trunk/debian-science/tasks/machine-learning&p2=projects/science/trunk/debian-science/tasks/machine-learning ============================================================================== --- projects/science/trunk/debian-science/tasks/machine-learning (original) +++ projects/science/trunk/debian-science/tasks/machine-learning Wed Jun 16 06:50:18 2010 @@ -68,30 +68,96 @@ Language: C/C++ WNPP: 585788 License: BSD +Pkg-Description: Library for Large Linear Classification + LIBLINEAR is a linear classifier for data with millions of instances and + features. It supports + . + * L2-regularized classifiers + L2-loss linear SVM, L1-loss linear SVM, and logistic regression (LR) + * L1-regularized classifiers (after version 1.4) + L2-loss linear SVM and logistic regression (LR) + . + Main features of LIBLINEAR include + . + * Same data format as LIBSVM + * similar usage to LIBSVM + * Multi-class classification: 1) one-vs-the rest, 2) Crammer & Singer + * Cross validation for model selection + * Probability estimates (logistic regression only) + * Weights for unbalanced data + * MATLAB/Octave interface Depends: libocas-dev Homepage: http://cmp.felk.cvut.cz/~xfrancv/ocas/html/ Language: C WNPP: 585789 License: GPL-3 +Pkg-Description: OCAS solver for training linear SVM classifiers + This library implements Optimized Cutting Plane Algorithm (OCAS) for training + linear SVM classifiers from large-scale data. The computational effort of OCAS + scales with O(m log m) where m is the sample size. In an extensive empirical + evaluation OCAS significantly outperforms current state of the art SVM solvers, + like SVM^light, SVM^perf and BMRM, achieving speedups of over 1,000 on some + datasets over SVM^light and 20 over SVM^perf, while obtaining the same precise + Support Vector solution. + . + * SVM solvers for training linear classifiers from large scale-data + * Binary (two-class) and genuine multi-class SVM formulations + * Optimized code written in C + * Reads examples from SVM^light format + * Optimized for both sparse and dense features + * Parallelized version of the binary solver + * binary solver) + * Tools for classification + * Training translation invariant image classifiers from virtual examples + * Functions for computing image features based on Local Binary Patterns + * (LBP) Depends: python-pyevolve Homepage: http://pyevolve.sourceforge.net Language: Python WNPP: 580924 License: PSF derivate +Pkg-Description: Complete genetic algorithm framework written in pure python + Pyevolve was developed to be a complete genetic algorithm framework written in + pure python. The main objectives of Pyevolve are: + . + * written in pure python - to maximize the cross-platform aspect + * easy to use API - the API must be easy to the end-user + * see the evolution - the user can and must see and interact with the + evolution statistics, graphs, etc. + * extensible - the API must be extensible, the user can create + new representations, genetic operators such as + crossover, mutation, etc. + * fast - the design must be optimized for performance + * common features - the framework must implement the most common + features: selectors like roulette wheel, + tournament, ranking, uniform. Scaling schemes + such as linear scaling, etc. + * default parameters - we must have default operators, settings, etc + in all options Depends: flann Homepage: http://www.cs.ubc.ca/~mariusm/index.php/FLANN/FLANN Language: C++ WNPP: 581903 License: BSD +Pkg-Description: Fast Library for Approximate Nearest Neighbors + FLANN is a library for performing fast approximate nearest neighbor searches + in high dimensional spaces. It contains a collection of algorithms we found + to work best for nearest neighbor search and a system for automatically + choosing the best algorithm and optimum parameters depending on the dataset. Depends: lua-torch5 Homepage: http://torch5.sourceforge.net Language: C, Lua WNPP: 490204 License: BSD +Pkg-Description: A matlab-like environment for state-of-the-art machine learning algorithms. + Torch5 provides a Matlab-like environment for state-of-the-art machine + learning algorithms. It is easy to use and provides a very efficient + implementation, thanks to an easy and fast scripting language (Lua) and + a underlying C implementation. Depends: lush Why: LUSH is a generic Lisp environment for numeric computation, but _______________________________________________ Blends-commit mailing list [email protected] http://lists.alioth.debian.org/mailman/listinfo/blends-commit
