Java Data Mining
Java Data Mining (JDM) is a standard Java API for developing data mining applications and tools. JDM defines an object model and Java API for data mining objects and processes. JDM enables applications to integrate data mining technology for developing predictive analytics applications and tools. The JDM 1.0 standard was developed under the Java Community Process as JSR 73. In 2006, the JDM 2.0 specification was being developed under JSR 247, but has been withdrawn in 2011 without standardization.
Various data mining functions and techniques like statistical classification and association, regression analysis, data clustering, and attribute importance are covered by the 1.0 release of this standard.
- AIDA (Abstract Interfaces for Data Analysis) is a language-neutral standard, with a Java implementation
- Mark F. Hornick, Erik Marcade, Sunil Venkayala: "Java Data Mining: Strategy, Standard, And Practice: A Practical Guide for Architecture, Design, And Implementation" (Broché)
- SCaViS Java data analysis and data mining framework that supports scripting languages
- Weka (machine learning)
- Apache Mahout
- Java Data Mining: Strategy, Standard, and Practice, Hornick, Marcadé, Venkayala, ISBN 0-12-370452-9
- JSR 247 (JDM 2.0)
- JSR 73 (JDM 1.0)
- Datamining (java.net project)
- Java Data Mining concepts article by Mark F. Hornick, Erik Marcadé, and Sunil Venkayala, at JavaWorld.com
- Mine Your Own Data with the JDM API article by Frank Sommers
- Using Java Data Mining to Develop Advanced Analytics Applications article by Sunil Venkayala at SYS-CON JDM Article
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