A Comparative Study of Data Mining Techniques for Preferences of Shopping at the Mall
Data analysis is a process used to discover useful information from dataset to make conclusions, and to support decision-making. In data mining classification is one of the widely used techniques for categorical data. Past studies indicate that analysis of preferences of Shopping at the mall gives better result using decision tree algorithm (Classification Techniques). The idea of this paper is to conduct the comparative analysis and gives the accuracy measures for classification techniques like decision tree and HP BN Classifier (HP- indicates High Performance) model for preferences of shopping at the mall dataset. This paper models the techniques using SAS Enterprise Miner and concludes which technique is fit for the given dataset. This paper used preferences of shopping at the mall dataset from various people lived in the urban area..