Heart Diseases Prediction Using Multiple Machine Learning Techniques

In this paper we focused on identifying heart disease of a patient, based on ten parameters found from a benchmark database of pathological reports. Here we use six machine learning techniques: K-means, Fuzzy C-means (FCM), Support Vector Machine(SVM), Fuzzy inference (FIS) clustering, Logistic Regression (LR) and Multiple Linear Regression (MLR) along with Neural Network(NN) as the binary data classification to detect the heart disease. Finally, we combined the methods under different combinations to enhance accuracy of detection of diseases, and the corresponding result is found above 94% for combination of FCM, K-mean, SVM, MLR, FIS and NN.