Authors: V. Prasathkumar, A. Deepalakshmi, N.Ramkumar
Abstract: Classification is a step by step procedure for designating a given piece of input into any of the given category. Classification is an important Machine Learning technique. There are many classification problem occurs in different application areas and need to be solved. Different types are classification algorithms like lazy, tree-based, rule-based, etc are widely used. This work studies the performance of different lazy classifiers for classification of Multivariate data set from UCI machine learning repository using the open source machine learning tool. A comparison of different lazy classifiers used and a practical guideline for selecting the most suited algorithm for a classification is presented in this work. Apart from that some empirical criteria for describing and evaluating the best classifiers are given.
Keywords: Classification; IB1 Classifier; IBk Classifier; K Star Classifier; LWL Classifier
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