Overview of PAKDD Competition 2007

Abstract

The PAKDD Competition 2007 involved the problem of predicting customers’ propensity to take up a home loan when a collection of data from credit card users are provided. It is rather difficult to address the problem because 1) the data set is extremely imbalanced; 2) the features are mixture types; and 3) there are many missing values. This article gives an overview on the competition, mainly consisting of three parts: 1) The background of the database and some statistical results of participants are introduced; 2) An analysis from the viewpoint of data preparation, resampling/reweighting and ensemble learning employed by different participants is given; and 3) Finally, some business insights are highlighted.