Weka (machine learning)
From Wikipedia, the free encyclopedia
Weka (Waikato Environment for Knowledge Analysis) is a suite of machine learning software written in Java at the University of Waikato which implements numerous machine learning algorithms from various learning paradigms.
Contents |
[edit] Description
The focus of the algorithms implemented in Weka is on pattern classification, regression, and clustering. In addition, several further algorithms are provided, including meta-level frameworks such as ensembles. Weka is free open-source software under the GNU General Public License (GPL).
Since 1993, Weka was developed at University of Waikato in New Zealand. In September 2006, the Weka project was acquired by Pentaho,[1] an open-source business intelligence software company.
[edit] See also
- YALE (Yet Another Learning Environment) Open-source machine learning framework implemented in Java fully integrating Weka
- List of numerical analysis software
[edit] References
[edit] External links
[edit] General
- Weka Project home page at University of Waikato in New Zealand
- Weka Project home page at SourceForge.net (SF.net)
- Pentaho
[edit] Weka project acquired by Pentaho
[edit] Examples of applications
- Gene selection from microarray data for cancer classification
- QSPR of metal complexation
- Classification of Expressed sequence tag (EST) data from plant/pathogen interface
 |
This software-related article is a stub. You can help Wikipedia by expanding it. |
