Svm Machine Learning

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, ... Platforms: Windows, Mac, Linux

This project provides a framework for testing and comparing different machine learning algorithms (particularly reinforcement learning methods) in different scenarios. Its intended area of application is in research and education. Platforms: Windows, Mac, Linux

Iracema is a Named Entity Recognition and Classification (NERC) library that aims to provide algorithms and commonly used functionality for both implementing and evaluating NERC systems. It is implemented in Java. Iracema features: * A Flexible architecture for implementing and evaluating NERC... Platforms: Mac

This application is an open-source machine learning program for supervised classification of patterns (vectors of measurements). PCP implements the following algorithms and methods: - Fisher's linear discriminant - dimensionality reduction using Singular Value Decomposition - Principal... Platforms: Windows, Mac, *nix, C/C++, BSD Solaris

Installation - Unpack in your modules folder (usually /sites/all/modules/) and enable under Administer > Site Building > Modules.  Requirements: - Drupal 6.x Platforms: Windows, Mac, *nix, PHP, BSD Solaris

The file demonstrates interfacing Java with Matlab by using weka (Machine learning software, written in JAVA) as an example. Platforms: Matlab

Scikit Learn is a free and open source machine learning framework written in the Python programming language. Here are some key features of "Scikit Learn": ?*A* supervised learning ?*A* classification ?*A* regression Platforms: Mac

Weka packahe provides a collection of machine learning algorithms for data mining tasks. The algorithms can either be applied directly to a dataset or called from your own Java code. Weka contains tools for data pre-processing, classification, regression, clustering, association rules, and... Platforms: Windows

Weka packahe provides a collection of machine learning algorithms for data mining tasks. The algorithms can either be applied directly to a dataset or called from your own Java code. Weka contains tools for data pre-processing, classification, regression, clustering, association rules, and... Platforms: Windows

Easy-to-use and general-purpose machine learning in Python scikits.learn is a Python module integrating classic machine learning algorithms in the tightly-knit world of scientific Python packages (numpy, scipy, matplotlib). It aims to provide simple and efficient solutions to learning problems... Platforms: *nix

Mind AI project is an artificial mind based on some advanced concepts: - machine learning - representation - meta representation of concepts - concept reflection - reification - denotation Interaction with the AI is done via IRC. Whats New in This Release: - geo: start some... Platforms: *nix

Learn data mining with easy-to-use examples. Teach computer to add, subtract, Boolean operations, Fishers Iris task and even chess moves with convenient application NeoNeuro Data Mining! You will be amazed how Data Mining learns chess step by step, like a child. Unlike neural nets NeoNeuro Data... Platforms: Windows, Windows 8, Windows 7, Windows Server

Inspired by neurons and their connections in the brain, neural network is a representation used in machine learning. After running the back-propagation learning algorithm on a given set of examples, the neural network can be used to predict outcomes for any set of input values. Neural Networks... Platforms: Windows

SpamBlazer uses machine learning techniques to extract pertinent rules automatically that dictate the legitimacy of an electronic email or otherwise. SpamBlazer understands the chameleonic nature of spammers and stays ahead of them by incorporating new data into its training set and discarding... Platforms: Windows, Windows Vista, 7

Waffles is a handy C++ development framework specially designed for researchers in machine learning, artificial intelligence, and data mining. The framework contains a class library of learning algorithms and other useful tools, and several demos that show how to build apps using the class... Platforms: Windows

Conrad is both a high performance Conditional Random Field engine which can be applied to a variety of machine learning problems and a specific set of models for gene prediction using semi-Markov CRFs. Platforms: Windows, Mac, Linux

Dataset Retrieval through Intelligent Agents (DARIA): is an Open Source project for facilitating the construction of ARFF data set files for use with WEKA or any such Machine Learning/Data Mining Software through the use of Intelligent Agents. Platforms: Windows, Mac, Linux

Platform for parallel computation in the Amazon cloud, including machine learning ensembles written in R for computational biology and other areas of scientific research. Home to MR-Tandem, a hadoop-enabled fork of X!Tandem peptide search engine. Platforms: Windows, Mac, Linux

The Java Data Mining Package (JDMP) is a library that provides methods for analyzing data with the help of machine learning algorithms (e.g. clustering, classification, graphical models, neural networks, Bayesian networks, text processing, optimization). Platforms: Windows, Mac, Linux

LPCforSOS is a machine learning framework with a special focus on structured output spaces and pairwise learning. It supports currently multiclass, ordinal, hierarchical, multi-label and label ranking classification settings. Platforms: Windows, Mac, Linux