Support vector machine the most fruitful algorithm for prognosticating heart disorder

Abstract

One of the wealthiest areas of research is Data mining that is more popular in healthcare organizations. Heart disease is the main outcome of death in the human society over the recent years. Heart disease is serious life threatening diseases that result to death. In order to save a pan-tient's life, the doctors and medical examiners are being taking many efforts. The consultant of doctor's determination can make without the advice of specialists because of the software develop by the advancement in computer technology. In most of the papers, Data mining tech-niques used in the existing method in the research are Naive Bayes, Decision tree, J48, K-Nearest Neighbor (K-NN) (or) Lazy IBK algo-rithms to predict heart diseases. In this paper, support vector machines (SVM) technique will produce the most accuracy prediction rate for heart diseases while comparing to all the other techniques used in data mining.

Fraud prediction for credit card using classification method

“…Hence, this is known as frauds in which one card is used by another. The person who tries to use card of another person is not having good intention as that person want to withdraw all money from user account [13]. The unauthorized user is identified with the help of fraud detection system, if one could commit the fraud.…”