Classification of Paddy by using Naive Bayesian Classifier

Abstract

Classification is a form of data analysis that can be used to extract models describing important data classes or to predict future data trends. Data classification is a two step process. In this system, a model is built on the training datasets by using the Naive Bayesian classification algorithm. And then, a model is used to test the unknown datasets. The performance of classifier is estimated by using the hold-out method. The Naive Bayesian (NB) classifiers have been one of the most popular techniques as basis of many classification applications both theoretically and practically. This system presents a Naive Bayesian classification learning in order to evolve useful subset of paddy features for classification task. This system is determined the kind of paddy by using Naive Bayesian classification.