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FRFE: Fast Recursive Feature Elimination for Credit Scoring

Ha, Van Sang and Nguyen, Ha Nam (2016) FRFE: Fast Recursive Feature Elimination for Credit Scoring. In: International Conference on Nature of Computation and Communication, 2016.

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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 ...

Item Type: Conference or Workshop Item (Paper)
Subjects: Information Technology (IT)
Divisions: Faculty of Information Technology (FIT)
Depositing User: Dr Hà Nam Nguyễn
Date Deposited: 24 Nov 2016 09:20
Last Modified: 24 Nov 2016 09:20

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