Abstract- Business intelligence (BI) technologies provide
historical, current, and predictive views of business operations.
Data mining is the core BI. This study uses data mining
techniques to analyses historical data of banking system. These
techniques including K-means method, fuzzy c-means clustering
method, self-organizing map and expected maximization
clustering algorithm are used to choose the best clustering
algorithm to segment customers into groups. Then the
Dominance-Based Rough Set Approach is applied to provide a
set of rules to classify customer in bank system. The induced
rules can provide recommendations of behaviors that increase
the risk in financial processes.
Keywords: K-means, Fuzzy c-mea |
