Prediction Model Using Micro-clustering

This study proposes a method of clarifying the purchase consciousness of customers by conceptualizing their awareness as consumers. Specifically, the method addresses the purchase record data of the customer, uses micro-clustering based on the data polishing technique to conceptualize the customer's mind according to the items that the customer has purchased, and uses a regularized regression model to build a prediction model based on the conceptualization. Micro-clustering is an algorithm for clustering graphs, and the data polishing technique clarifies the unclear hidden dense structures in the graph so that we can exhaustly enumerate with simple methods. By this method, we can obtain clusters of strongly correlated items, which are commonly purchased, are obtained. The clusters represent the customers’ minds, and thus we used them to build a classification model in an application; a model with the predictor variables representing the customers of health-conscious