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 Semi-supervised data sets

Introduction
Experimental studies related

This section shows some relevant research papers in which some of the Semi-supervised classification 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: 2014 (1)

Year 2014 (1):

I. Triguero, S. Garcia, and F.Herrera, Self-Labeled Techniques for Semi-Supervised Learning: Taxonomy, Software and Empirical Study. Knowledge and Information Systems, in press (2014)

Link to: Data sets, algorithms and experimental results.