The Analysis Performance of Heart Failure Classification by Using Machine Learning Techniques

Abstract: Heart failure means that the heart is not pumping well as normal as it should be. Congestive heart failure is a form of heart failure that involves seeking timely medical care, although the two terms are sometimes used interchangeably. Heart failure happens when the heart muscle does not pump blood as well as it can, often referred to as congestive heart failure. Some disorders, such as heart's narrowed arteries (coronary artery disease) or high blood pressure, eventually make heart too weak or rigid to fill and pump effectively. Early detection of heart failure by using data mining techniques have gained its popularity among researchers. This research use some classification techniques for heart failure classification from medical data. This research analysed the performance of some classification algorithms, namely Support Vector Machine (SVM), Decision Forest (DF) and Boosted Decision Tree (BDT) to classify accurately heart failure risk data as input. At the end of this research,  the best algorithm among the three is discovered for heart failure classification.