Matches in SemOpenAlex for { <https://semopenalex.org/work/W3209489113> ?p ?o ?g. }
Showing items 1 to 75 of
75
with 100 items per page.
- W3209489113 abstract "Machine learning is a strategy that enable computers to automatize information-driven model building and programming through a scientific discovery of statistically important patterns within the obtainable data. The learning capability of a machine and the ability to do predictive analysis is very obligatory in this age of vast information. In this study, we focused on banking sector where too many individuals are applying for bank credits. Though, it is really troublesome to determine whom loan should be granted or whom should be rejected. For banking organizations acceptance of loan is a main task. The prediction model that we formed in this paper for predicting fraudulent loan requests. In this paper, we were working with six algorithms - Decision tree, Support vector machine, Random forest, K nearest neighbors, Ada-Boost, and Logistic regression to predict the fraudulent loan request from customers. We got 83.75% accuracy from K-Nearest Neighbors algorithm which was better than other five machine learning approaches." @default.
- W3209489113 created "2021-11-08" @default.
- W3209489113 creator A5010641284 @default.
- W3209489113 creator A5052566782 @default.
- W3209489113 creator A5060904816 @default.
- W3209489113 creator A5061963089 @default.
- W3209489113 date "2021-07-06" @default.
- W3209489113 modified "2023-09-23" @default.
- W3209489113 title "Machine Learning Algorithm to Predict Fraudulent Loan Requests" @default.
- W3209489113 cites W1985546543 @default.
- W3209489113 cites W2011441697 @default.
- W3209489113 cites W2028543020 @default.
- W3209489113 cites W2097933633 @default.
- W3209489113 cites W2114675416 @default.
- W3209489113 cites W2331466950 @default.
- W3209489113 cites W2529306290 @default.
- W3209489113 cites W2561309841 @default.
- W3209489113 cites W2979883048 @default.
- W3209489113 cites W2980161170 @default.
- W3209489113 cites W2980306573 @default.
- W3209489113 cites W2998729480 @default.
- W3209489113 cites W3047560809 @default.
- W3209489113 doi "https://doi.org/10.1109/icccnt51525.2021.9579517" @default.
- W3209489113 hasPublicationYear "2021" @default.
- W3209489113 type Work @default.
- W3209489113 sameAs 3209489113 @default.
- W3209489113 citedByCount "0" @default.
- W3209489113 crossrefType "proceedings-article" @default.
- W3209489113 hasAuthorship W3209489113A5010641284 @default.
- W3209489113 hasAuthorship W3209489113A5052566782 @default.
- W3209489113 hasAuthorship W3209489113A5060904816 @default.
- W3209489113 hasAuthorship W3209489113A5061963089 @default.
- W3209489113 hasConcept C10138342 @default.
- W3209489113 hasConcept C119857082 @default.
- W3209489113 hasConcept C12267149 @default.
- W3209489113 hasConcept C127413603 @default.
- W3209489113 hasConcept C144133560 @default.
- W3209489113 hasConcept C151956035 @default.
- W3209489113 hasConcept C154945302 @default.
- W3209489113 hasConcept C169258074 @default.
- W3209489113 hasConcept C201995342 @default.
- W3209489113 hasConcept C2777764128 @default.
- W3209489113 hasConcept C2780451532 @default.
- W3209489113 hasConcept C41008148 @default.
- W3209489113 hasConcept C84525736 @default.
- W3209489113 hasConceptScore W3209489113C10138342 @default.
- W3209489113 hasConceptScore W3209489113C119857082 @default.
- W3209489113 hasConceptScore W3209489113C12267149 @default.
- W3209489113 hasConceptScore W3209489113C127413603 @default.
- W3209489113 hasConceptScore W3209489113C144133560 @default.
- W3209489113 hasConceptScore W3209489113C151956035 @default.
- W3209489113 hasConceptScore W3209489113C154945302 @default.
- W3209489113 hasConceptScore W3209489113C169258074 @default.
- W3209489113 hasConceptScore W3209489113C201995342 @default.
- W3209489113 hasConceptScore W3209489113C2777764128 @default.
- W3209489113 hasConceptScore W3209489113C2780451532 @default.
- W3209489113 hasConceptScore W3209489113C41008148 @default.
- W3209489113 hasConceptScore W3209489113C84525736 @default.
- W3209489113 hasLocation W32094891131 @default.
- W3209489113 hasOpenAccess W3209489113 @default.
- W3209489113 hasPrimaryLocation W32094891131 @default.
- W3209489113 hasRelatedWork W3127425528 @default.
- W3209489113 hasRelatedWork W4200437006 @default.
- W3209489113 hasRelatedWork W4205958290 @default.
- W3209489113 hasRelatedWork W4246246790 @default.
- W3209489113 hasRelatedWork W4281846282 @default.
- W3209489113 hasRelatedWork W4293191462 @default.
- W3209489113 hasRelatedWork W4312707991 @default.
- W3209489113 hasRelatedWork W4320483443 @default.
- W3209489113 hasRelatedWork W4321636153 @default.
- W3209489113 hasRelatedWork W4376059206 @default.
- W3209489113 isParatext "false" @default.
- W3209489113 isRetracted "false" @default.
- W3209489113 magId "3209489113" @default.
- W3209489113 workType "article" @default.