FRINK Linked Data Fragments server

Matches in SemOpenAlex for { <https://semopenalex.org/work/W3009609110> ?p ?o ?g. }

• W3009609110 endingPage "113351" @default.
• W3009609110 startingPage "113351" @default.
• W3009609110 abstract "Abstract Lenders, such as banks and credit card companies, use credit scoring models to evaluate the potential risk posed by lending money to customers, and therefore to mitigate losses due to bad credit. The profitability of the banks thus highly depends on the models used to decide on the customer’s loans. State-of-the-art credit scoring models are based on machine learning and statistical methods. One of the major problems of this field is that lenders often deal with imbalanced datasets that usually contain many paid loans but very few not paid ones (called defaults). Recently, dynamic selection methods combined with ensemble methods and preprocessing techniques have been evaluated to improve classification models in imbalanced datasets presenting advantages over the static machine learning methods. In a dynamic selection technique, samples in the neighborhood of each query sample are used to compute the local competence of each base classifier. Then, the technique selects only competent classifiers to predict the query sample. In this paper, we evaluate the suitability of dynamic selection techniques for credit scoring problem, and we present Reduced Minority k-Nearest Neighbors (RMkNN), an approach that enhances state of the art in defining the local region of dynamic selection techniques for imbalanced credit scoring datasets. This proposed technique has a superior prediction performance in imbalanced credit scoring datasets compared to state of the art. Furthermore, RMkNN does not need any preprocessing or sampling method to generate the dynamic selection dataset (called DSEL). Additionally, we observe an equivalence between dynamic selection and static selection classification. We conduct a comprehensive evaluation of the proposed technique against state-of-the-art competitors on six real-world public datasets and one private one. Experiments show that RMkNN improves the classification performance of the evaluated datasets regarding AUC, balanced accuracy, H-measure, G-mean, F-measure, and Recall." @default.
• W3009609110 created "2020-03-13" @default.
• W3009609110 creator A5054358438 @default.
• W3009609110 creator A5059923683 @default.
• W3009609110 creator A5065118727 @default.
• W3009609110 creator A5076068546 @default.
• W3009609110 creator A5082554104 @default.
• W3009609110 date "2020-08-01" @default.
• W3009609110 modified "2023-10-17" @default.
• W3009609110 title "A novel approach to define the local region of dynamic selection techniques in imbalanced credit scoring problems" @default.
• W3009609110 cites W1982211005 @default.
• W3009609110 cites W1988844742 @default.
• W3009609110 cites W2005596732 @default.
• W3009609110 cites W2015406385 @default.
• W3009609110 cites W2016944307 @default.
• W3009609110 cites W2052611008 @default.
• W3009609110 cites W2093829413 @default.
• W3009609110 cites W2098154993 @default.
• W3009609110 cites W2099454382 @default.
• W3009609110 cites W2100208452 @default.
• W3009609110 cites W2100805904 @default.
• W3009609110 cites W2105776892 @default.
• W3009609110 cites W2125877832 @default.
• W3009609110 cites W2131816657 @default.
• W3009609110 cites W2137959503 @default.
• W3009609110 cites W2145940431 @default.
• W3009609110 cites W2148143831 @default.
• W3009609110 cites W2156357252 @default.
• W3009609110 cites W2160767978 @default.
• W3009609110 cites W2278519563 @default.
• W3009609110 cites W2336505047 @default.
• W3009609110 cites W2461391084 @default.
• W3009609110 cites W2473172823 @default.
• W3009609110 cites W2562319768 @default.
• W3009609110 cites W2562923621 @default.
• W3009609110 cites W2586297576 @default.
• W3009609110 cites W2761075141 @default.
• W3009609110 cites W2761700016 @default.
• W3009609110 cites W2783336591 @default.
• W3009609110 cites W2792895843 @default.
• W3009609110 cites W2793304295 @default.
• W3009609110 cites W2800788706 @default.
• W3009609110 cites W2895142658 @default.
• W3009609110 cites W2898153843 @default.
• W3009609110 cites W4212883601 @default.
• W3009609110 doi "https://doi.org/10.1016/j.eswa.2020.113351" @default.
• W3009609110 hasPublicationYear "2020" @default.
• W3009609110 type Work @default.
• W3009609110 sameAs 3009609110 @default.
• W3009609110 citedByCount "21" @default.
• W3009609110 countsByYear W30096091102020 @default.
• W3009609110 countsByYear W30096091102021 @default.
• W3009609110 countsByYear W30096091102022 @default.
• W3009609110 countsByYear W30096091102023 @default.
• W3009609110 crossrefType "journal-article" @default.
• W3009609110 hasAuthorship W3009609110A5054358438 @default.
• W3009609110 hasAuthorship W3009609110A5059923683 @default.
• W3009609110 hasAuthorship W3009609110A5065118727 @default.
• W3009609110 hasAuthorship W3009609110A5076068546 @default.
• W3009609110 hasAuthorship W3009609110A5082554104 @default.
• W3009609110 hasBestOaLocation W30096091102 @default.
• W3009609110 hasConcept C119857082 @default.
• W3009609110 hasConcept C124101348 @default.
• W3009609110 hasConcept C154945302 @default.
• W3009609110 hasConcept C41008148 @default.
• W3009609110 hasConcept C81917197 @default.
• W3009609110 hasConceptScore W3009609110C119857082 @default.
• W3009609110 hasConceptScore W3009609110C124101348 @default.
• W3009609110 hasConceptScore W3009609110C154945302 @default.
• W3009609110 hasConceptScore W3009609110C41008148 @default.
• W3009609110 hasConceptScore W3009609110C81917197 @default.
• W3009609110 hasLocation W30096091101 @default.
• W3009609110 hasLocation W30096091102 @default.
• W3009609110 hasOpenAccess W3009609110 @default.
• W3009609110 hasPrimaryLocation W30096091101 @default.
• W3009609110 hasRelatedWork W2961085424 @default.
• W3009609110 hasRelatedWork W3046775127 @default.
• W3009609110 hasRelatedWork W3107474891 @default.
• W3009609110 hasRelatedWork W3170094116 @default.
• W3009609110 hasRelatedWork W3209574120 @default.
• W3009609110 hasRelatedWork W4205958290 @default.
• W3009609110 hasRelatedWork W4286629047 @default.
• W3009609110 hasRelatedWork W4306321456 @default.
• W3009609110 hasRelatedWork W4306674287 @default.
• W3009609110 hasRelatedWork W4224009465 @default.
• W3009609110 hasVolume "152" @default.
• W3009609110 isParatext "false" @default.
• W3009609110 isRetracted "false" @default.
• W3009609110 magId "3009609110" @default.
• W3009609110 workType "article" @default.