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dc.contributor.authorS, Kavitha-
dc.contributor.authorG, Sangeetha-
dc.date.accessioned2020-09-14T07:35:14Z-
dc.date.available2020-09-14T07:35:14Z-
dc.date.issued2019-09-27-
dc.identifier.urihttp://localhost:8080/xmlui/handle/123456789/1469-
dc.description.abstractIn day to day life the requirement of food is increasing at rapid rate and hence the farmers, government and researchers are using several techniques in agriculture for the improvement in production. Plants are usually affected by a many pests and diseases. In the process of resolving agricultural issues the concepts of data mining plays a fundamental part. Research in agriculture is increasing due to development of technologies and forth coming challenges [1]. In improving the general growth of a country the plant disease detection has an important place. Diseases in plants, production and loss can be predicted with the help of data mining approaches like classification. The future trends in agricultural processes can be forecasted with the Data mining techniques. Generally the damages were examined by using classifiers namely SVM , K-Nearest Neighbor, Decision Tree, Random Forest, Naive Bayes and so on. [13].en_US
dc.language.isoenen_US
dc.publisherKarpagam Academy of Higher Educationen_US
dc.subjectAgricultureen_US
dc.subjectclassificationen_US
dc.titleAN ANALYSIS ON CROP YIELD PREDICTION USING DATA MINING TECHNIQUESen_US
dc.title.alternativeNational Conference on Recent Trends and Advances in the Field of Information Technologyen_US
dc.typeBooken_US
Appears in Collections:National Conference

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