Investigating the Performance of Naive- Bayes Classifiers and K- Nearest Neighbor Classifiers

@article{Islam2007InvestigatingTP,
  title={Investigating the Performance of Naive- Bayes Classifiers and K- Nearest Neighbor Classifiers},
  author={Mohammed J. Islam and Q. M. Jonathan Wu and Majid Ahmadi and Maher A. Sid-Ahmed},
  journal={2007 International Conference on Convergence Information Technology (ICCIT 2007)},
  year={2007},
  pages={1541-1546}
}
Probability theory is the framework for making decision under uncertainty. In classification, Bayes' rule is used to calculate the probabilities of the classes and it is a big issue how to classify raw data rationally to minimize expected risk. Bayesian theory can roughly be boiled down to one principle: to see the future, one must look at the past. Naive Bayes classifier is one of the mostly used practical Bayesian learning methods. K-nearest neighbor is a supervised learning algorithm where… CONTINUE READING
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