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An Improved Algorithm for Bayes Classifier to Handle Correlated Attributes
| International Journal of Computer Applications |
| Foundation of Computer Science (FCS), NY, USA |
| Volume 71 - Number 8 |
| Year of Publication: 2013 |
| Authors: Sharmishtha Panagare, Kshitij Pathak |
10.5120/12381-8732
|
Sharmishtha Panagare, Kshitij Pathak . An Improved Algorithm for Bayes Classifier to Handle Correlated Attributes. International Journal of Computer Applications. 71, 8 ( June 2013), 33-36. DOI=10.5120/12381-8732
Abstract
Classification can be defined as a target function which maps attribute value of objects to predefined class. One objective is to divide the objects into proper group and other objective is to predict the class of unknown records. Bayesian classifier classifies and predicts the class of objects on the basis of posterior probability based on some prior probability. Earlier work does not handle the effect of correlated attributes on the performance and the accuracy of classifier. In this paper a novel approach using association rules is defined to predict the class of unknown records even if the attributes are correlated. In medical and health care systems it is necessary to generate an outcome which can work well in all conditions and give the beneficial results.
References
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- www. r. projrct. org
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