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Ilter et al., 2019 - Google Patents

Feature selection approaches for machine learning classifiers on yearly credit scoring data

Ilter et al., 2019

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Document ID
1610805848237485807
Author
Ilter D
Kocadağlı O
Ravishanker N
Publication year
Publication venue
Recent Advances in Data Science and Business Analytics

External Links

Snippet

Credit scoring is one of the efficient methods to measure systematic risk when financing individual customers in the banking sector. While past literature mainly focused on cross- sectional data at a given time, there is increasing interest in credit scoring based on …
Continue reading at www.researchgate.net (PDF) (other versions)

Classifications

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    • G06K9/62—Methods or arrangements for recognition using electronic means
    • G06K9/6217—Design or setup of recognition systems and techniques; Extraction of features in feature space; Clustering techniques; Blind source separation
    • G06K9/6232—Extracting features by transforming the feature space, e.g. multidimensional scaling; Mappings, e.g. subspace methods
    • G06K9/6247—Extracting features by transforming the feature space, e.g. multidimensional scaling; Mappings, e.g. subspace methods based on an approximation criterion, e.g. principal component analysis
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    • G06Q40/00—Finance; Insurance; Tax strategies; Processing of corporate or income taxes
    • G06Q40/02—Banking, e.g. interest calculation, credit approval, mortgages, home banking or on-line banking
    • G06Q40/025—Credit processing or loan processing, e.g. risk analysis for mortgages
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    • G06Q40/00—Finance; Insurance; Tax strategies; Processing of corporate or income taxes
    • G06Q40/08—Insurance, e.g. risk analysis or pensions
    • G—PHYSICS
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    • G06Q10/00—Administration; Management
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