Abstract: Data mining and multiagent approach has been used successfully in the development of large complex systems. Agents are used to perform some action or activity on behalf of a user of a computer system. The study proposes an agent based algorithm PrePZero-r using Zero-R algorithm in Weka. Algorithms are powerful technique for solution of various combinatorial or optimization problems. Zero-R is a simple and trivial classifier, but it gives a lower bound on the performance of a given dataset which should be significantly improved by more complex classifiers. The Proposed Algorithm called PrePZero-r has significantly reduced time taken to build the model than Zero-R algorithm by removing the Lower Bound Values 0 while preprocessing and comparing the result with class values. Also proposed study introduced new factor “Accuracy (1-e)” for each individual attribute.

Inamdar S A, Narangale S.M. and G. N. Shinde. “Preprocessor Agent Approach to Knowledge Discovery Using Zero-R Algorithm”. International Journal of Advanced Computer Science and Applications (IJACSA) 2.12 (2011). http://dx.doi.org/10.14569/IJACSA.2011.021212

@article{A2011,
title = {Preprocessor Agent Approach to Knowledge Discovery Using Zero-R Algorithm},
journal = {International Journal of Advanced Computer Science and Applications},
doi = {10.14569/IJACSA.2011.021212},
url = {http://dx.doi.org/10.14569/IJACSA.2011.021212},
year = {2011},
publisher = {The Science and Information Organization},
volume = {2},
number = {12},
author = {Inamdar S A and Narangale S.M. and G. N. Shinde}
}