A Comparative Study of Different Data Mining Algorithms

Abstract

Data Mining is used extensively in many sectors today, viz., business, health, security, informatics etc. The successful application of data mining algorithms can be seen in marketing, retail, and other sectors of the industry. The aim of this paper is to present the readers with the various data mining algorithms which have wide applications. This paper focuses on four data mining algorithms K-NN, Naïve Bayes Classifier, Decision tree and C4.5. An attempt has been made to do a comparative study on these four algorithms on the basis of theory, its advantages and disadvantages, and its applications. After studying all these algorithms in detail, we came to a conclusion that the accuracy of these techniques depend on various characteristics such as: type of problem, dataset and performance matrix.