KEEL: A software tool to assess evolutionary algorithms for Data Mining problems (regression, classification, clustering, pattern mining and so on)

KEEL-dataset - Experimental studies with Missing values data sets

Introduction
Experimental studies related

This section shows some relevant research papers in which some of the missing values data sets avalaible in KEEL-dataset have been employed.

For each study, we provide its reference (plain text and BibTeX formats), abstract and summary. A pdf version the article can also be downloaded. Additionally, we offer complementary material about the experimental studies carried up: Algorithms tested, data sets employed and results obtained (XLS and CVS formats).

Experimental studies and results with these data sets

Jump to year: 2010 (1)

Year 2010 (1):

J. Luengo, S. García, F. Herrera, A Study on the Use of Imputation Methods for Experimentation with Radial Basis Function Network Classifiers Handling Missing Attribute Values: The good synergy between RBFs and EventCovering method. Neural Networks 23 406-418, doi:10.1016/j.neunet.2009.11.014.

Link to: Data sets, algorithms and experimental results.