Evaluation of Attribute Selection Methods for Decision Tree Classification

In this modern era of Information and Communication Technology (ICT), huge data of high dimensions has been produced through various transactions and sensors. These data sets which are further used for data mining have large number of attributes and instances. Attribute selection methods are used to select relevant attributes for mining from this high dimensional data. This study explores the idea of attribute selection so that there is improvement in the performance with minor efforts. It is an attempt to evaluate the attribute selection methods using weka.