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Seminar Details


Date 9-5-2006
Time 11:00
Room/Location Sala conferenze, num. 322 - 3 piano
Title Evolutionary Rough Feature Selection in Gene Expression Data: An Application to Bioinformatics
Speaker Dr. Haider Banka,
Affiliation Indian Statistical Institute Kolkata, India
Link http://www.isical.ac.in/
Abstract Feature Selection refers to the selection of input attributes that are most predictive of a given outcome. This is a problem encountered in many areas such as machine learning, signal processing, and recently bioinformatics/computational biology. Feature selection is one of the most important and challenging tasks, when it comes to dealing with large datasets with thousands of variables. Areas of web-mining and gene expression array analysis provide examples, where selection of interesting and useful features determines the performance of subsequent analysis. The intrinsic nature of noise, uncertainty, incompleteness of data makes extraction of hidden and useful information very difficult. Capability of handling imprecision, inexactness and noise, has attracted researchers to use rough sets for feature selection. This presentation will cover a recent application of hybridized system using rough set and Multi-objective GA based feature selection technique for analysing high dimensional Gene expression data from Bioinformatics.
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