Comparative Study on Classification Techniques to Identify Potential Customers

This work focuses on applying data mining techniques to a practical example of cross-selling problem raised by PAKDD'07 Data Mining Competition. Firstly, we build decision tree from high dimensional data to identify the most important features according to information gain. Some comprehensible business insights are also gained from it. Secondly, a novel re-sampling technique is proposed to resolve the imbalanced dataset problem. Thirdly, we apply MLP + n-tuple classifier to build prediction model. Finally, experiments and results are presented to evaluate the performance of our approach.