%0 Journal Article %1 IJACSA.2011.021212 %A Inamdar S A Narangale S.M., G N Shinde %D 2011 %J International Journal of Advanced Computer Science and Applications(IJACSA) %K Bound Class Data Lower Value; Zero-R algorithm; mining; values. %N 12 %T Preprocessor Agent Approach to Knowledge Discovery Using Zero-R Algorithm %U http://ijacsa.thesai.org/ %V 2 %X 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.

@article{IJACSA.2011.021212, 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.}, added-at = {2014-02-21T08:00:08.000+0100}, author = {{Inamdar S A Narangale S.M.}, G N Shinde}, biburl = {https://www.bibsonomy.org/bibtex/2f6ef77179788e26866c9c641d7904afc/thesaiorg}, interhash = {0598311cf7b6d4c6852812b8f7fd34e6}, intrahash = {f6ef77179788e26866c9c641d7904afc}, journal = {International Journal of Advanced Computer Science and Applications(IJACSA)}, keywords = {Bound Class Data Lower Value; Zero-R algorithm; mining; values.}, number = 12, timestamp = {2014-02-21T08:00:08.000+0100}, title = {{Preprocessor Agent Approach to Knowledge Discovery Using Zero-R Algorithm}}, url = {http://ijacsa.thesai.org/}, volume = 2, year = 2011 }