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Open data mining platform. Provides common architecture for algorithms of various types. Efficient processing of arbitrarily large volumes of data thanks to data streaming. Weka and Rseslib partially integrated. (www.debellor.org)
weka outlier is an implementation of outlier detection algorithms for WEKA.
CODB (Class Outliers: Distance-Based) Algorithm is the first algorithm developed using WEKA framework.
MuSE-CIR is a Multigram-based Search Engine and Collaborative Information Retrieval system. Written in Java /JSP, supports any JDBC connectable database - thoroughly tested only with OracleXE, and somewhat with MySQL, JSP on Apache Tomcat 5.5
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.
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The Decision Tree Learning algorithm ID3 extended with pre-pruning for WEKA, the free open-source Java API for Machine Learning. It achieves better accuracy than WEKA's ID3, which lacks pre-pruning.Info: http://bruno-wp.blogspot.com/search/label/Softwar
A discretization algorithm based on the Minimum Description Length. Implemented as a filter according to the standards and interfaces of WEKA, the Java API for Machine Learning. More Info: http://bruno-wp.blogspot.com/search/label/Software
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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/.
AstroWeka is a set of extentions to Weka, a popular data mining program, which which allows it to work directly with astronomical data in the Virtual Observatory.
JUDGE (Java Utility for Document Genre Eduction) features automatic classification and clustering of documents, optionally as a webservice.
The program is written entirely in Java and makes use of the Weka machine learning toolkit.
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.
Weka-Parallel is a modification to Weka, created with the intention of being able to harness the power of Weka and the speed of parallel processing to be able to run a number of data mining and machine learning algorithms quickly.
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.