Empirical Evaluation of Classifiers’ Performance Using Data Mining Algorithm

  IJCTT-book-cover
 
International Journal of Computer Trends and Technology (IJCTT)          
 
© 2015 by IJCTT Journal
Volume-21 Number-3
Year of Publication : 2015
Authors : Sanjay Kumar Sen, Dr. Sujata Dash
  10.14445/22312803/IJCTT-V21P128

MLA

Sanjay Kumar Sen, Dr. Sujata Dash"Empirical Evaluation of Classifiers’ Performance Using Data Mining Algorithm". International Journal of Computer Trends and Technology (IJCTT) V21(3):146-155, March 2015. ISSN:2231-2803. www.ijcttjournal.org. Published by Seventh Sense Research Group.

Abstract -
The field of data mining and knowledge discovery in databases (KDD) has been growing in leaps and bounds, and has shown great potential for the future[10]. Data classification is an important task in KDD (knowledge discovery in databases) process. It has several potential applications. The performance of a classifier is strongly dependent on the learning algorithm. In this paper, we describe our experiment on data classification considering several classification models. We tabulate the experimental results and present a comparative analysis thereof.

References
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Keywords
Knowledge discovery in databases, classifier, data classification.