Heart Disease Prediction System Using Anova, Pca and Svm Classification

Heart disease is a term that assigns to a large number of healthcare conditions related to heart. These medical conditions describe the unexpected health conditions that directly control the heart and all its parts. The main objective of this research is to develop an efficient heart disease prediction system using feature extraction and SVM classifier that can be used to predict the occurrence of heart disease. The heart disease prediction system helps the physician and healthcare professionals as a tool for heart disease diagnosis. To protect the life of a patient from heart diseases there have to be quick and efficient prediction technique such as PCA with SVM classification technique is to be followed. This technique is widely used to validate the accuracy of medical data. By providing the effective treatments, it also helps to reduce the treatment costs. Keywords— KDD, Heart Disease Prediction, Data Mining, Classifiers, PCA, Support Vector Machine.