HEART DISEASE PREDICTION USING DATA MINING TECHNIQUES: A SURVEY
Abstract
Heart disease is a common cause of death for people around the world. The overall examination on reasons for death because of coronary illness has been watched that it is the real reason for death. Analysis of these issues at beginning period helps the doctors in treating it at starting stage and to enhance the patient's wellbeing. In this manner the need to treat coronary illness that is found in individuals which precise entangled issues, if overlooked at beginning time. Different Data Mining Techniques can be used to analyze heart related issues. The essential point is an analysis of the Data Mining technique which is generally exact. There are different types of Data Mining Techniques such as Decision Tree, Naïve Bayesian, Support Vector Machine (SVM),K-NN classifier,Hybrid Approach, ArtificialNeural Network ANN). In this paper, we analyze different classification algorithms.
Keywords
Heart disease, Data Mining Techniques, Decision Tree, Naïve Bayesian, Support Vector Machine (SVM), K-NN classifier, Hybrid Approach, Artificial Neural Network (ANN).
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PDFDOI: https://doi.org/10.26483/ijarcs.v9i2.5872
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