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Machine learning based classifiers used quite often for predicting forest cover types, are the Naïve Bayes classifier, the k-Nearest Neighbors classifier, and the Random forest classifier. This paper is directed towards examining all of these classifiers coupled with feature selection and attribute derivation in order to evaluate which one is best suited for forest cover type classification. Numerous...
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