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

Luis Niebles-Mamani; Rodrigo Velarde-Herencia; José Sulla-Torres

doi:10.18687/LACCEI2017.1.1.329

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, José Sulla-Torres

Professional School of Systems Engineering

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

1 Scopus citations

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 contribution	Prediction of non-payment of credit card customers, with application of the k-nearest neighbors algorithm and Clas-FriedmanAligned-ST
Original language	Spanish
Title of host publication	15th LACCEI International Multi-Conference for Engineering, Education Caribbean Conference for Engineering and Technology
Subtitle of host publication	Global Partnership for Development and Engineering Education, LACCEI 2017
Editors	Humberto Alvarez, Maria M. Larrondo Petrie
Publisher	Latin American and Caribbean Consortium of Engineering Institutions
ISBN (Electronic)	9780999344309
DOIs	https://doi.org/10.18687/LACCEI2017.1.1.329
State	Published - 2017
Event	15th LACCEI International Multi-Conference for Engineering, Education Caribbean Conference for Engineering and Technology, LACCEI 2017 - Boca Raton, United States Duration: 19 Jul 2017 → 21 Jul 2017

Publication series

Name	Proceedings of the LACCEI international Multi-conference for Engineering, Education and Technology
Volume	2017-July
ISSN (Electronic)	2414-6390

Conference

Conference	15th LACCEI International Multi-Conference for Engineering, Education Caribbean Conference for Engineering and Technology, LACCEI 2017
Country/Territory	United States
City	Boca Raton
Period	19/07/17 → 21/07/17

Access to Document

10.18687/LACCEI2017.1.1.329

Cite this

Niebles-Mamani, L., Velarde-Herencia, R., & Sulla-Torres, J. (2017). Predicción de incumplimiento de pago de clientes de tarjetas de crédito, con aplicación del algoritmo del k-vecino más cercano y Clas-FriedmanAligned-ST. In H. Alvarez, & M. M. L. Petrie (Eds.), 15th LACCEI International Multi-Conference for Engineering, Education Caribbean Conference for Engineering and Technology: Global Partnership for Development and Engineering Education, LACCEI 2017 (Proceedings of the LACCEI international Multi-conference for Engineering, Education and Technology; Vol. 2017-July). Latin American and Caribbean Consortium of Engineering Institutions. https://doi.org/10.18687/LACCEI2017.1.1.329

Niebles-Mamani, Luis ; Velarde-Herencia, Rodrigo ; Sulla-Torres, José. / Predicción de incumplimiento de pago de clientes de tarjetas de crédito, con aplicación del algoritmo del k-vecino más cercano y Clas-FriedmanAligned-ST. 15th LACCEI International Multi-Conference for Engineering, Education Caribbean Conference for Engineering and Technology: Global Partnership for Development and Engineering Education, LACCEI 2017. editor / Humberto Alvarez ; Maria M. Larrondo Petrie. Latin American and Caribbean Consortium of Engineering Institutions, 2017. (Proceedings of the LACCEI international Multi-conference for Engineering, Education and Technology).

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title = "Predicci{\'o}n de incumplimiento de pago de clientes de tarjetas de cr{\'e}dito, con aplicaci{\'o}n del algoritmo del k-vecino m{\'a}s cercano y Clas-FriedmanAligned-ST",

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.",

keywords = "Credit rating, Evolutionary algorithms, Lazy learning",

author = "Luis Niebles-Mamani and Rodrigo Velarde-Herencia and Jos{\'e} Sulla-Torres",

note = "Publisher Copyright: {\textcopyright} 2017 Latin American and Caribbean Consortium of Engineering Institutions. All rights reserved.; 15th LACCEI International Multi-Conference for Engineering, Education Caribbean Conference for Engineering and Technology, LACCEI 2017 ; Conference date: 19-07-2017 Through 21-07-2017",

year = "2017",

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publisher = "Latin American and Caribbean Consortium of Engineering Institutions",

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Niebles-Mamani, L, Velarde-Herencia, R & Sulla-Torres, J 2017, Predicción de incumplimiento de pago de clientes de tarjetas de crédito, con aplicación del algoritmo del k-vecino más cercano y Clas-FriedmanAligned-ST. in H Alvarez & MML Petrie (eds), 15th LACCEI International Multi-Conference for Engineering, Education Caribbean Conference for Engineering and Technology: Global Partnership for Development and Engineering Education, LACCEI 2017. Proceedings of the LACCEI international Multi-conference for Engineering, Education and Technology, vol. 2017-July, Latin American and Caribbean Consortium of Engineering Institutions, 15th LACCEI International Multi-Conference for Engineering, Education Caribbean Conference for Engineering and Technology, LACCEI 2017, Boca Raton, United States, 19/07/17. https://doi.org/10.18687/LACCEI2017.1.1.329

Predicción de incumplimiento de pago de clientes de tarjetas de crédito, con aplicación del algoritmo del k-vecino más cercano y Clas-FriedmanAligned-ST. / Niebles-Mamani, Luis; Velarde-Herencia, Rodrigo; Sulla-Torres, José.
15th LACCEI International Multi-Conference for Engineering, Education Caribbean Conference for Engineering and Technology: Global Partnership for Development and Engineering Education, LACCEI 2017. ed. / Humberto Alvarez; Maria M. Larrondo Petrie. Latin American and Caribbean Consortium of Engineering Institutions, 2017. (Proceedings of the LACCEI international Multi-conference for Engineering, Education and Technology; Vol. 2017-July).

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

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AU - Velarde-Herencia, Rodrigo

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AB - 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.

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Niebles-Mamani L, Velarde-Herencia R, Sulla-Torres J. Predicción de incumplimiento de pago de clientes de tarjetas de crédito, con aplicación del algoritmo del k-vecino más cercano y Clas-FriedmanAligned-ST. In Alvarez H, Petrie MML, editors, 15th LACCEI International Multi-Conference for Engineering, Education Caribbean Conference for Engineering and Technology: Global Partnership for Development and Engineering Education, LACCEI 2017. Latin American and Caribbean Consortium of Engineering Institutions. 2017. (Proceedings of the LACCEI international Multi-conference for Engineering, Education and Technology). doi: 10.18687/LACCEI2017.1.1.329

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

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