Van Sang Ha and Ha Nam Nguyen (2016) FRFE: Fast Recursive Feature Elimination for Credit Scoring. In: International Conference on Nature of Computation and Communication, 2016.
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Official URL: http://link.springer.com/chapter/10.1007/978-3-319...
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)|
|Deposited By:||Dr Hà Nam Nguyễn|
|Deposited On:||24 Nov 2016 09:20|
|Last Modified:||24 Nov 2016 09:20|
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