Title :
WEKA: a machine learning workbench
Author :
Holmes, Geoffrey ; Donkin, Andrew ; Witten, Ian H.
Author_Institution :
Dept. of Comput. Sci., Waikato Univ., Hamilton, New Zealand
fDate :
29 Nov-2 Dec 1994
Abstract :
WEKA is a workbench for machine learning that is intended to aid in the application of machine learning techniques to a variety of real-world problems, in particular, those arising from agricultural and horticultural domains. Unlike other machine learning projects, the emphasis is on providing a working environment for the domain specialist rather than the machine learning expert. Lessons learned include the necessity of providing a wealth of interactive tools for data manipulation, result visualization, database linkage, and cross-validation and comparison of rule sets, to complement the basic machine learning tools
Keywords :
agriculture; data analysis; data visualisation; learning (artificial intelligence); software tools; WEKA machine learning workbench; agricultural domains; data manipulation; database linkage; domain specialist; horticultural domains; interactive tools; machine learning tools; real-world problems; result visualization; rule set comparison; rule set cross-validation; working environment; Application software; Computer science; Couplings; Data visualization; Expert systems; Libraries; Machine learning; Machine learning algorithms; User interfaces; Visual databases;
Conference_Titel :
Intelligent Information Systems,1994. Proceedings of the 1994 Second Australian and New Zealand Conference on
Conference_Location :
Brisbane, Qld.
Print_ISBN :
0-7803-2404-8
DOI :
10.1109/ANZIIS.1994.396988