Preprocessor Agent Approach to Knowledge Discovery Using Zero-R Algorithm

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