Date of Publication :22nd February 2018
Abstract: The support vector machine (SVM) is a well-known algorithm for binary classification problems. SVM was originally developed to classify only two classes. In the real world, most of the applications involve multiclass classification e.g. plant disease detection, face detection, plant classification etc. Binary SVM can be extended in different ways for multi-class classification problems. This paper provides a survey of different multi-class approaches like One vs. one, one vs. rest, Directed Acyclic Graph (DAG) and Error Corrected Output Coding (ECOC). The paper also presents how Multi SVM is effectively used to early detect and classify the plant diseases based on plant leaf symptoms. The early detection of plant disease ultimately effects on crop production which is the major factor of the Indian economy.
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