Selecting Salient Features and Samples Simultaneously to Enhance Cross-Selling Model Performance

The rapid growth in information science and technology has lead to generation of huge amount of valuable data in many areas. In finance for example, over the past five years, many banks have experienced exceptional growth in service and have built up bank’s Group Data Warehouse. In order to realize faster, more effective decisions and provide more excellent customer services, new technologies to handle or extract fully the latent knowledge within the data are urgently required. The finance company that donated the data for 2007 PAKDD competition would like to build a cross-selling model to predict the potential take-ups of cross-selling home loans to its credit card customers (Qiu, Wang & Bi, 2008). abstract