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.
Full text not available from this repository.Abstract
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 |
| URI: | http://eprints.uet.vnu.edu.vn/eprints/id/eprint/1939 |
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