Abstract
Out of many different diseases, cancer and cardiac disease cover around the world day by day. For the diagnosis of these two diseases many different techniques have been used. Still the research is continuing. In recent research Machine Learning technique is mostly utilized for better accuracy. In this work eight different abnormalities are analyzed for possible disease detection. Statistical technique is utilized for feature extraction. Earlier to Feature Extraction the raw signal is normalized to Low Pass filter. For comparative purposes, five distinct features such as mean, median, standard deviation, energy, and Entropy are used as input to three different machine learning classifiers K-Nearest Neighbor (KNN), Decision Tree (DT), and Support Vector Machine (SVM). Finally, comparison table are shown in the result section. It is found that the SVM classifier in terms of training and testing perform well as compare to KNN and DT classifier.
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