Predicción de incumplimiento de pago de clientes de tarjetas de crédito, con aplicación del algoritmo del k-vecino más cercano y Clas-FriedmanAligned-ST

Translated title of the contribution: Prediction of non-payment of credit card customers, with application of the k-nearest neighbors algorithm and Clas-FriedmanAligned-ST

Luis Niebles-Mamani, Rodrigo Velarde-Herencia, Jose Alfredo Sulla Torres

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

Abstract

Companies that give credit cards to clients face some problems such as non-payment, which is why companies need to control such debts, so as to minimize the risk of recovery of the investment, as a result of debtor clients. In this article, the lazy learning algorithm KNN with the method of statistical evaluation Clas- FriedmanAligned-ST was used, to help us to predict the degree of nonpayment of debts, in order to optimize and improve the prediction performed by data mining algorithms. The database used for this work contains 30000 records, each defined by 25 attributes, of which a significant sample of 5439 instances was taken, with 24 fields. A data processing model is developed, the results are discussed; And concludes with the benefits of evolutionary computing application.

Translated title of the contributionPrediction of non-payment of credit card customers, with application of the k-nearest neighbors algorithm and Clas-FriedmanAligned-ST
Original languageSpanish
Title of host publication15th LACCEI International Multi-Conference for Engineering, Education Caribbean Conference for Engineering and Technology
Subtitle of host publicationGlobal Partnership for Development and Engineering Education, LACCEI 2017
EditorsHumberto Alvarez, Maria M. Larrondo Petrie
PublisherLatin American and Caribbean Consortium of Engineering Institutions
ISBN (Electronic)9780999344309
DOIs
StatePublished - 2017
Event15th LACCEI International Multi-Conference for Engineering, Education Caribbean Conference for Engineering and Technology, LACCEI 2017 - Boca Raton, United States
Duration: 19 Jul 201721 Jul 2017

Publication series

NameProceedings of the LACCEI international Multi-conference for Engineering, Education and Technology
Volume2017-July
ISSN (Electronic)2414-6390

Conference

Conference15th LACCEI International Multi-Conference for Engineering, Education Caribbean Conference for Engineering and Technology, LACCEI 2017
Country/TerritoryUnited States
CityBoca Raton
Period19/07/1721/07/17

Bibliographical note

Publisher Copyright:
© 2017 Latin American and Caribbean Consortium of Engineering Institutions. All rights reserved.

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