| Abstract | Diseases in fruit cause wrecking issue in economic misfortunes and production in
agricultural industry around the world. Disease management by physically is a
challenging task. A large portion of the diseases are seen on the leaves or stems of the
plant. Hence agriculturist needs to discover the efficient techniques. To reduce the cost of
production and enhance the quality and amount of any fruit. It will be extremely valuable
for the farmers to detect the disease in beginning time. Data mining is the process of
discovering and extracting of intriguing patterns and knowledge from a lot of data. There
are various data mining strategies to anticipate the distinctive fruit diseases. In this paper
the k-means clustering, k-nearest neighbor, support vector machine algorithms are
examined.
Keywords: Data mining, k-means clustering, k-nearest neighbor, support vector machine
algorithm, Feature Extraction.
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