Business Intelligence Commons^™

A Hybrid Data Mining Approach For Identifying The Temporal Effects Of Variables Associated With Breast Cancer Survival, Serhat Simsek, Ugur Kursuncu, Eyyub Kibis, Musheera Anisabdellatif, Ali Dag

Department of Information Management and Business Analytics Faculty Scholarship and Creative Works

Predicting breast cancer survival is crucial for practitioners to determine possible outcomes and make better treatment plans for the patients. In this study, a hybrid data mining based methodology was constructed to differentiate the variables whose importance for survival change over time. Therefore, the importance of variables was determined for three different time periods (i.e. one, five, and ten years). To conduct such an analysis, the most parsimonious models were constructed by employing one regression analysis method—Least Absolute Shrinkage and Selection Operator (LASSO), and one metaheuristic optimization method, namely a Genetic Algorithm (GA). Due to the high imbalance between the …