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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