Search Results for "weka mac"

A framework for learning from a continuous supply of examples, a data stream. Includes classification, regression, clustering, outlier detection and recommender systems. Related to the WEKA project, also written in Java, while scaling to adaptive large scale machine learning.

JCLALtext is a class library designed to extend the framework JCLAL text tasks. JCLALtext is free, open source and developed with the Java programming language. JCLALtext is distributed under the GNU license. The researcher can use the class library by adding it to your project.

GISBox by Citiviz is a ready-to-use virtual appliance containing an assortment of powerful, free and open source GIS, Data Mining and Analysis, Modelling and Programming software and packages. The pre-configured and tested GISBox allows you to try and use in few minutes a variety of software used by data scientists, engineers, physicists, mathematicians, geomatics engineers, and geographers from around the globe, without installing anything more than once the Oracle VirtualBox™ software...

Genetic Programming (tree structure) predictor within Weka data mining software for both continuous and classification problems.

Weka.Net is a port to .Net of the Weka library. It use all the power of .net including some redisene of the library to make more Object-Oriented.

Agent Academy is a Java integrated development framework for creating Intelligent Agents and Multi Agent Systems. Agent Academy seamlessly integrates JADE and WEKA platforms and enables the creation of software agents that use Data Mining models.

KNN-WEKA provides a implementation of the K-nearest neighbour algorithm for Weka. Weka is a collection of machine learning algorithms for data mining tasks. For more information on Weka, see http://www.cs.waikato.ac.nz/ml/weka/.

A utility to extract data from RDBMSs and convert into .arff file format required by WEKA data mining tool set, both interactive wizard and batch working modes.

ktdata is a C++ library for accessing tabular data, like from CSV files. Its goals are: 1. object design 2. portability (Linux and Windows support at least) 3. high performance 4. support for common data file formats, like CSV, ARFF (Weka), etc.