文章基本信息

标题：Comparative Analysis of Genetic Algorithm Based Approach for Gene Cancer Classification using prominent features with PSO for Dimensionality Reduction and FFBNN as Classifier
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作者：Vaishali P Khobragade ; M.Anup Kumar
期刊名称：International Journal of Computer Science and Information Technologies
电子版ISSN：0975-9646
出版年度：2014
卷号：5
期号：6
页码：8015-8021
出版社：TechScience Publications
摘要：The advancement in genome technology has change the outlook of the researchers in the field of gene cancer classification. These developed techniques mainly comprises of, dimensionality reduction, feature selection, and gene classification for the ;process of gene cancer classification.. In our work, microarray gene classification by GA with FFBNN was proposed for precise classification of genes to their corresponding gene types. But, it is not sure that the GA and FFBNN will perform their operations properly in gene classification process. Thus, analysis is necessary for the techniques that are utilized in the gene classification process. Hence, in this study, we present a comparative analysis of familiar methods that are utilized in the microarray gene classification process. We compare the GA with FFBNN approach with that of PSO with FFBNN .The performances of the classification methods are evaluated by the performance measures such as accuracy, specificity, and sensitivity. Moreover, the classification performance of each method is compared with the other methods to validate the high score performance in microarray gene classification
关键词：Microarray gene expression; Classification;Dimensionality Reduction; Feature Selection; Genetic;Algorithm (GA); Feed Forward Back propagation Neural;Network (FFBNN)Partial Swarm Optimizer(PSO).