A STUDY ON DISEASE SUBTYPES TO IDENTIFY TOP RANKED GENES DISCRIMINATION AND BUILDING GENE ASSOCIATED NETWORKS OF OBESITY MICROARRAY DATASET USING MACHINE LEARNING AND STATISTICAL METHODS

ABSTRACT Data mining is a field of information and knowledge discovery and it is started to be an interest target for information industry, because of the existence of enormous data containing large amounts of unknown knowledge. Classification is one of the most widely used methods of data mining in healthcare. The classification algorithms can be useful to forecasting the outcome of some diseases or its discover the genetic performance of growth. The proposed research work focuses on classifying the obesity microarray dataset using SVM classifier to identify the significant genes, discrimination among different classes present in the dataset and also the interaction among genes by building gene networks.