Comparative Study of Classification Algorithms for Big Data in VANET

Classification is a method used to predict membership of specific instance into a group of data. It uses a supervised learning method. Various of classification algorithm are available to process data, but the issue is which one is preferred taking consideration of the different input parameters. In this paper, we choose the several major supervised algorithms: K-NN (K Nearest Neighbors), NB (Naive Bays) and DT (Decision Tree). We use Vehicle Ad Hoc Network (VANET) real time data. This paper focuses on study of effectiveness measures in terms of accuracy and runtime.