Analysis of Different Similarity Functions with Fuzzy C-Means Clustering Approach Using Meeting Transcripts
more �9ei�o���knowledge.The aim of this work is to create a MLPT, to predict Myocardial Infraction. After getting the patient information this MLPT, forecastthat the patient is caused by heart attack or not which is performed by using three Data mining techniques: Naïve Bayes, Decision tree and WAC (Weighted Associative Classifiers). Using the medical prognosis such as chest pain type, thalassic, slope etc., it can predict the probabilities of patients getting a heart disease in the future. The prediction is performed from extracting the patient’s diachronic data or data storage. The research is mainly developed to recover the hidden information from the database. The system has been implemented in JSP and checked using the datasets that is been collected from UCI machine learning repository.
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