The k-feature set problem is W[2]-complete
Journal of Computer and System Sciences - Special issue on Parameterized computation and complexity
Consistency-based search in feature selection
Artificial Intelligence
Redundancy based feature selection for microarray data
Proceedings of the tenth ACM SIGKDD international conference on Knowledge discovery and data mining
Applying memetic algorithms to the analysis of microarray data
EvoWorkshops'03 Proceedings of the 2003 international conference on Applications of evolutionary computing
EC'05 Proceedings of the 3rd European conference on Applications of Evolutionary Computing
Integer linear programming for Constrained Multi-Aspect Committee Review Assignment
Information Processing and Management: an International Journal
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Novel, high-throughput technologies are challenging the core of algorithmic methods available in Computer Science. Microarray technologies give Life Sciences researchers the opportunity to simultaneously measure thousands of gene expression levels under different conditions or coming from different cell lines. With appropriate data mining models and algorithms, this would lead to a systematic exploration of molecular classification of cancer, just one among many other exciting applications. The aim of this paper is to present a unified mathematical formalization for different feature selection problems and investigate their performance in classification of cancer cell-lines. We also present some results using the NCI60 dataset.