[2012] A hybrid feature selection for fault prediction

Posted by sanghv on 07/09/2013 in Feature selection |

Software fault prediction plays a vital role in software quality assurance. Identifying the faulty modules helps to better concentrate on those modules and helps improve the quality of the software. With increasing complexity of software nowadays feature selection is important to remove the redundant, irrelevant and erroneous data from the dataset. In general, Feature selection […]

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Filter- versus Wrapper-based Feature Selection For credit scoring

Posted by sanghv on 07/09/2013 in Credit risk, Feature selection, Financial Risk, Machine Learning |

We address the problem of credit scoring as a classification and feature subset selection problem. Based on the current framework of sophisticated feature selection methods, we identify features that contain the most relevant information to distinguish good loan payers from bad loan payers. The feature selection methods are validated on several real world datasets with […]

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