Abstract: Agriculture plays an indispensable role in the development of the country especially in the growing country like India where most of the people’s revenue is generated from agriculture. Disease affected crops leads to the loss of crop productivity. Therefore, leaf disease prediction in apple cultivation is of considerable importance to overcome these problems. The proposed work intends to predict different disease in apple leaf like apple scab and marssonina using different algorithms like K nearest neighbor(KNN),support vector machine(SVM), classification decision tree, regression decision tree and Naïve Bayes. From the simulation result, it can be concluded that KNN performs better as compared to other algorithms in terms of accuracy of disease prediction.
Keywords: SVM, KNN, Apple disease, Marssonina, Naïve Bayes, inverse, Apple scab.
Title: Apple Leaves Disease Detection Using Machine Learning Approach
Author: Kulbir Kaur Sandhu
International Journal of Computer Science and Information Technology Research
ISSN 2348-1196 (print), ISSN 2348-120X (online)
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