A Comparative Study and Analysis of Classification Methodologies in Data Mining for Energy Resources

Abstract

Retrieval of right sequence in extensive quantity of records in irrelevant, unreported and concealed data by applying the process of data mining methods. Classification is a procedure used for building classification models for a set of input data. This study is about to compare and analyze the various classification algorithms for energy resources using Weka tool. In this study, it uses five different data mining methods, namely iterative classifier optimizer, Bayes net, classifier via regression, LMT and JRip. The diverse attainment of the algorithm is found by the assess of variables like true conclusive, false conclusive, exactness, reminiscence and ratio. Meticulousness of algorithm is examined using the values of correctly classified occurrences and incorrectly classified occurrences.