Clustering and Predictive Modeling: An Ensemble Approach

Abstract

Today’s data storage and collection abilities have allowed the accumulation of enormous amounts of data. Data mining can be a useful tool in transforming these large amounts of raw data into useful information. Predictive modeling is a very popular area in data mining. The results of these type tasks can contain helpful information that can be used in decision making. Ensemble method techniques involve using the results of multiple models in combination. Research has shown that by applying an ensemble method approach to predictive modeling one can increase the model’s accuracy. However, these techniques focus on classification data mining algorithms. This research investigates the notion of using a data clustering and predictive modeling approach to increase predictive model accuracy.