Online ISSN- 2457-0818

Vol 2, No 3 (2017)

Mental Health Disease using Classification Approach in Data Mining

Authors: Shilpa Kanoongo, Shubhi Shrivastava

Abstract: Data mining is the best method for finding out the Prediction of data through various sources. It Provide the information about the methodology we are presenting. Through data mining techniques, useful evidence can be collected from such source, which can help fitness seekers to get immediate support for their fitness related problems. This paper presents investigation on small data mining method mainly in mental disease dataset. Three various algorithms of data mining i.e. KNN, SVM, Naïve Bayes are applied on a disease dataset, to analyze the performance of the classifiers. The predictive rate is evaluated using four evaluation parameters i.e. Correctness, exactness, recollection and measuring point. The implementation is performed in Matlab 7.15 tool shows that Naïve Bayes outdoes as compared to remaining classifiers. This gives performance measure in various techniques in a single dataset and also comparison with previous result.

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