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Effectiveness Prediction of Memory Based Classifiers for the Classification of Multivariate Data Set

Authors

C. Lakshmi Devasena, Sphoorthy Engineering College, India

Abstract

Classification is a step by step practice for allocating a given piece of input into any of the given category. Classification is an essential Machine Learning technique. There are many classification problem occurs in different application areas and need to be solved. Different types are classification algorithms like memory-based, tree-based, rule-based, etc are widely used. This work studies the performance of different memory based classifiers for classification of Multivariate data set from UCI machine learning repository using the open source machine learning tool. A comparison of different memory based classifiers used and a practical guideline for selecting the most suited algorithm for a classification is presented. Apart from that some empirical criteria for describing and evaluating the best classifiers are discussed.

Keywords

Classification, IB1 Classifier, IBk Classifier, K Star Classifier, LWL Classifier

Full Text  Volume 2, Number 4