AN EFFICIENT HYBRID CLASSIFICATION ALGORITHM FOR HEART PREDICTION IN DATA MININIG
European Journal of Molecular & Clinical Medicine,
2020, Volume 7, Issue 4, Pages 1945-1954
AbstractHeart sickness is the major critical reasons of mortality in the globe today. The gauge of coronary illness is a most basic test in the clinical information investigation zone. A few strategies are proposed to discover the result of ailment at prior stage which is as yet getting looked at. The Data mining is generally used to separate the critical, significant and wanted information from the patient's datasets. The few characterization techniques are utilized in the customary strategies for the coronary illness forecast in which the information mining ascribes are taken care of it. In this paper, to obtain a optimal result and also for the prediction of heart disease in the earlier stage, the novel hybrid FA-KNN are proposed. The proposed FA-KNN is the hybrid combination of machine learning algorithm of K-nearest neighbour and the optimization method of Firefly Algorithm which has been analyzed that produces the best result for all types of health related datasets. Therefore, the outcome of FA-KNN provides the optimal results in terms of precision, accuracy and recall with the evaluation of conventional methods.
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