ATTRIBUTE ANALYSIS METHODOLOGIES BY FINDING CORRELATIONS AND WEIGHT ESTIMATION FOR OPTIMAL ANALYSIS IN WEKA

Abstract

We’ll use the Road Accident Data collected from Data repository available on web stores. The tasks performed in previous studies are to generate the final result on the dataset. We’ll also find the result but mainly we analyze that what attribute is more important in decision making process. We’ll perform some operation on data, then we’ll identify that particular attributes throughout the dataset. For this purposes we would use the Naive Bayesian Classifier. A good accuracy was in the primary motive to proceed further with this work. Naive bayes classifier is a revolutionary approach in the data analysis and classification domain which provides better accuracies. The dataset should be made like so that algorithms can be applied to get optimal results. We have compared the existing work and consider their problem formulation to get overcome with optimizing results. A road accident is something which misshapen with our mistakes or road infrastructure so we have chosen dataset regarding all the issue and attributes and applied Weka over it.