Abstract:
Feature selection, the process of removing irrelevant features can be extremely useful in reducing the dimensionality of the data to be processed, in reducing execution t...Show MoreMetadata
Abstract:
Feature selection, the process of removing irrelevant features can be extremely useful in reducing the dimensionality of the data to be processed, in reducing execution time and improving predictive accuracy of the classifier. Selecting the right set of features for classification is one of the most important problems in designing a good classifier. Feature selection methods can be decomposed into two broad classes. One is Filter methods and another is Wrapper method. This paper proposes hybrid method which is based on the Mutual Information and Genetic Algorithm.
Published in: 2013 International Conference on Advances in Computing, Communications and Informatics (ICACCI)
Date of Conference: 22-25 August 2013
Date Added to IEEE Xplore: 21 October 2013
ISBN Information: