PREDICTING PERFORMANCE OF CLASSIFICATION ALGORITHMS

Classification is the most commonly applied data mining method, and is used to develop models that can classify large amounts of data to predict the best performance. Identifying the best classification algorithm among all available is a challenging task. This paper presents a performance comparative study of the most widely used classification algorithms. Moreover, the performances of these algorithms have been analyzed by using different data sets. Three different datasets from University of California, Irvine (UCI) are compared with different classification techniques. Each technique has been evaluated with respect to accuracy and execution time and performance evaluation has been carried out with selected classification algorithms. The WEKA machine learning tool is used to analysis of these three different data sets based on applying these classification methods to selected datasets and predicting the best performance results.