Search Results for "feature selection"

Java Machine Learning Library is a library of machine learning algorithms and related datasets. Machine learning techniques include: clustering, classification, feature selection, regression, data pre-processing, ensemble learning, voting, ...

THE NEW, 11/7/2013 VERSION OF MOLCRUNCH IS HERE Molcrunch is an atomic or molecular electronic properties computational package. It provides Gaussian and Slater orbital support for SCF, MCSCF, and orthogonal or nonorthogonal orbital CI calculations. Its most sophisticated feature is a configuration manipulation CI package that provides symmetry filtering, orbital occupation selection, and a choice of many other wave function and/or basis characteristics. The symmetry filtering includes the ability to deal directly with certain non-Abelian groups as well as all Abelian groups. Linear systems can be treated exactly within the full continuous D-infinity-h or C-infinity-v groups. ...

A PHP script with maps of the World, China, Canada, USA, India, Africa and Europe that allows the user to select the countries, provinces or states by clicking on them or selecting a checkboxes. Selection causes the entity to turn a default color which contrasts with defaults colors of all bordering countries. Thus a patchwork is made to show the history of countries, states or provinces traveled. Added features allow users to download their maps, to blow them up to posters of any...

mlpy is a Python module for Machine Learning built on top of NumPy/SciPy and of GSL. mlpy provides high-level functions and classes allowing, with few lines of code, the design of rich workflows for classification, regression, clustering and feature selection. mlpy is free software; you can redistribute it and/or modify it under the terms of the GNU General Public License version 3. mlpy is available both for Python >=2.6 and Python 3.X.

DimReduction project provide an open-source multiplatform (Java) graphical environment for bioinformatics problems that supports many feature selection algorithms, pattern recognition techniques, criterion functions and graphic visualization tools.

Java port and extension of MLC++ 2.0 by Kohavi et al. Currently contains ID3, C4.5, Naive (aka Simple) Bayes, and FSS and CHC (genetic algorithm) wrappers for feature selection. WEKA 3 interfaces are in development.