Information gain directed genetic algorithm wrapper feature selection for credit rating

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dc.contributor.authorJadhav, Swati
dc.contributor.authorHe, Hongmei
dc.contributor.authorJenkins, Karl W.
dc.date.accessioned2020-04-02T16:06:07Z
dc.date.available2020-04-02T16:06:07Z
dc.date.freetoread2020-04-02
dc.date.issued2018-04-22
dc.description.abstractFinancial credit scoring is one of the most crucial processes in the finance industry sector to be able to assess the credit-worthiness of individuals and enterprises. Various statistics-based machine learning techniques have been employed for this task. “Curse of Dimensionality” is still a significant challenge in machine learning techniques. Some research has been carried out on Feature Selection (FS) using genetic algorithm as wrapper to improve the performance of credit scoring models. However, the challenge lies in finding an overall best method in credit scoring problems and improving the time-consuming process of feature selection. In this study, the credit scoring problem is investigated through feature selection to improve classification performance. This work proposes a novel approach to feature selection in credit scoring applications, called as Information Gain Directed Feature Selection algorithm (IGDFS), which performs the ranking of features based on information gain, propagates the top m features through the GA wrapper (GAW) algorithm using three classical machine learning algorithms of KNN, Naïve Bayes and Support Vector Machine (SVM) for credit scoring. The first stage of information gain guided feature selection can help reduce the computing complexity of GA wrapper, and the information gain of features selected with the IGDFS can indicate their importance to decision making.en_UK
dc.identifier.citationJadhav S, Hongmei H, Jenkins K. (2018) Information gain directed genetic algorithm wrapper feature selection for credit rating. Applied Soft Computing, Volume 69, August 2018, pp. 541-553en_UK
dc.identifier.cris20209388
dc.identifier.issn1568-4946
dc.identifier.urihttps://doi.org/10.1016/j.asoc.2018.04.033
dc.identifier.urihttps://dspace.lib.cranfield.ac.uk/handle/1826/15364
dc.language.isoenen_UK
dc.publisherElsevieren_UK
dc.rightsAttribution-NonCommercial-NoDerivatives 4.0 International*
dc.rights.urihttp://creativecommons.org/licenses/by-nc-nd/4.0/*
dc.subjectFeature selectionen_UK
dc.subjectGenetic algorithm in wrapperen_UK
dc.subjectSupport vector machineen_UK
dc.subjectK nearest neighbour clusteringen_UK
dc.subjectNaive Bayes classifieren_UK
dc.subjectROC curveen_UK
dc.titleInformation gain directed genetic algorithm wrapper feature selection for credit ratingen_UK
dc.typeArticleen_UK

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