ENVIRONMENTAL PREDICTION SYSTEM USING NAÏVE BAYES’ CLASSIFIER |
Author(s): |
Rupali Borse |
Keywords: |
Bayes Theorem, Naive Bayesian Classifier, Feature Selection, Irrelevant and Redundant Attributes. |
Abstract |
Feature selection is a key pre-preparing procedure for choosing more pertinent highlights and destroying the repetitive qualities. Finding the more important highlights for the objective is a fundamental movement to enhance the prescient exactness of the learning calculations since more superfluous highlights in the first element space will cause more order mistakes and expend more opportunity for learning. Numerous techniques have been proposed for highlight significance investigation however no work has been finished utilizing Bayes Theorem, Thus this venture has been started to present a class of play and no play likelihood by utilizing Naïve bayes arrangement. The principle goal of acquainting this approach is with improve the prescient precision of the Naive Bayesian Classifier. |
Other Details |
Paper ID: IJSARTV Published in: Volume : 4, Issue : 5 Publication Date: 5/2/2018 |
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