Data mining means to search the data from large amount of database. Classification is one of the well-known supervised learning techniques in data mining. We introduce three independent mining algorithm Navie Bayes (NB), Support Vector Machine (SVM) and Decision Tree(DT) classifier during the classification to improve precision, recall, f-measure and accuracy rates. These three algorithms, NB, SVM and DT classifier are useful and efficient, has been tested in medical dataset for heart disease and solving classification problem in data mining. In this paper, we compare the three different algorithms and the results indicate that decision tree algorithm has achieved a high accuracy rate of 91.3% and error rate 8.7% out of other algorithms. © Research India Publications.