%A Van Sang Ha
%A Ha Nam Nguyen
%T FRFE: Fast Recursive Feature Elimination for Credit Scoring
%X Abstract Credit scoring is one of the most important issues in financial decision-making. The use of data mining techniques to build models for credit scoring has been a hot topic in recent years. Classification problems often have a large number of features, but not all of them are useful for classification. Irrelevant and redundant features in credit data may even reduce the classification accuracy. Feature selection is a process of selecting a subset of relevant features, which can decrease the dimensionality, reduce the running time, and  ...
%D 2016
%P 133-142
%L SisLab1939