Paper Info
Title
KEEL: a software tool to assess evolutionary algorithms for data mining problems
Abstract
This paper introduces a software tool named KEEL which is a software tool to assess evolutionary algorithms for Data Mining problems of various kinds including as regression, classification, unsupervised learning, etc. It includes evolutionary learning algorithms based on different approaches: Pittsburgh, Michigan and IRL, as well as the integration of evolutionary learning techniques with different pre-processing techniques, allowing it to perform a complete analysis of any learning model in comparison to existing software tools. Moreover, KEEL has been designed with a double goal: research and educational.
Year
DOI
Venue
2009
10.1007/s00500-008-0323-y
Soft Comput.
Keywords
Field
DocType
experimental design,evolutionary learning,complete analysis,evolutionary algorithm,knowledge extraction,data mining problem,graphical programming,existing software tool,software tool,evolutionary computation,different pre-processing technique,data min- ing,unsupervised learning,java,different approach,machine learning.,evolutionary learning technique,computer-based education,evolutionary computing,machine learning,data mining
Interactive evolutionary computation,Data mining,Human-based evolutionary computation,Evolutionary robotics,Computer science,Evolutionary computation,Genetic programming,Unsupervised learning,Artificial intelligence,Evolutionary programming,Evolutionary music,Machine learning
Journal
Volume
Issue
ISSN
13
3
1433-7479
Citations 
PageRank 
References 
358
9.69
37
Authors
12
Search Limit
100358
Name
Order
Citations
PageRank
J. Alcalá-Fdez1205974.03
L. Sánchez243719.68
S. G. Garcia356924.88
M. J. del Jesus488431.15
S. Ventura582534.87
J. M. Garrell671028.39
José Otero755224.66
Cristóbal Romero82226148.97
Jaume Bacardit9109147.21
V. Rivas1053223.12
J. C. Fernández1136111.55
Francisco Herrera12273911168.49