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Bioinformatics. 2005 May 1;21(9):1964-70. Epub 2005 Jan 20.

Small, fuzzy and interpretable gene expression based classifiers.

Author information

1
Decision Systems Group, Brigham and Women's Hospital, Harvard Medical School/Massachusetts Institute of Technology, Boston, USA. staal@dsg.harvard.edu

Abstract

MOTIVATION:

Interpretation of classification models derived from gene-expression data is usually not simple, yet it is an important aspect in the analytical process. We investigate the performance of small rule-based classifiers based on fuzzy logic in five datasets that are different in size, laboratory origin and biomedical domain.

RESULTS:

The classifiers resulted in rules that can be readily examined by biomedical researchers. The fuzzy-logic-based classifiers compare favorably with logistic regression in all datasets.

AVAILABILITY:

Prototype available upon request.

PMID:
15661797
DOI:
10.1093/bioinformatics/bti287
[Indexed for MEDLINE]

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