Selective gaussian naïve bayes model for diffuse large-b-cell lymphoma classification: some improvements in preprocessing and variable elimination

Authors:
Andrés Cano;Javier G. Castellano;Andrés R. Masegosa;Serafín Moral
Affiliations:
Dept. Computer Science and Artificial Intelligence, University of Granada, Granada, Spain;Dept. Computer Science and Artificial Intelligence, University of Granada, Granada, Spain;Dept. Computer Science and Artificial Intelligence, University of Granada, Granada, Spain;Dept. Computer Science and Artificial Intelligence, University of Granada, Granada, Spain
Venue:
ECSQARU'05 Proceedings of the 8th European conference on Symbolic and Quantitative Approaches to Reasoning with Uncertainty
Year:
2005

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Abstract

In this work, we present some significant improvements for for feature selection in wrapper methods. They are two: the first of them consists in a proper preordering of the feature set; and the second one consists in the application of an irrelevant feature elimination method, where the irrelevance condition is subjected to the partial selected feature subset by the wrapper method. We validate these approaches with the Diffuse Large B-Cell Lymphoma subtype classification problem and we show that these two changes are an important improvement in the computation cost and the classification accuracy of these wrapper methods in this domain.