Predicción para el negocio de alquiler de automóviles con técnicas supervisadas

Sandra Zapata-Quentasi; Alba Yauri-Ituccayasi; Rodrigo Huamani-Avendaño; Jose Alfredo Sulla Torres

doi:10.18687/LACCEI2019.1.1.371

Predicción para el negocio de alquiler de automóviles con técnicas supervisadas

Translated title of the contribution: Prediction for the car rental business with supervised techniques

Sandra Zapata-Quentasi, Alba Yauri-Ituccayasi, Rodrigo Huamani-Avendaño, Jose Alfredo Sulla Torres

Departamento Académico de Ingeniería de Sistemas e Informática

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

Abstract

Car rental is a new trend and is already a reality in many countries, as it is a cheaper option than maintaining your own. The objective of this article is to identify the ideal car for a person, according to the characteristics that you want. In the present work, a study was made of the previous steps involved in the prediction of a car according to the desired characteristics and a comparison of the classification algorithms was carried out to determine which classification is appropriate in terms of the accuracy of the prediction. The steps followed were: Data collection, preprocessing, data preparation and comparison of classification algorithms. The results obtained show that the Random Forest algorithm presents a 95.12% correct classification of the instances and a mean square error of 0.12, which are acceptable results for the tests performed.

Translated title of the contribution	Prediction for the car rental business with supervised techniques
Original language	Spanish
Title of host publication	17th LACCEI International Multi-Conference for Engineering, Education, and Technology
Subtitle of host publication	"Industry, Innovation, and Infrastructure for Sustainable Cities and Communities", LACCEI 2019
Publisher	Latin American and Caribbean Consortium of Engineering Institutions
ISBN (Electronic)	9780999344361
DOIs	https://doi.org/10.18687/LACCEI2019.1.1.371
State	Published - 2019
Event	17th LACCEI International Multi-Conference for Engineering, Education, and Technology, LACCEI 2019 - Montego Bay, Jamaica Duration: 24 Jul 2019 → 26 Jul 2019

Publication series

Name	Proceedings of the LACCEI international Multi-conference for Engineering, Education and Technology
Volume	2019-July
ISSN (Electronic)	2414-6390

Conference

Conference	17th LACCEI International Multi-Conference for Engineering, Education, and Technology, LACCEI 2019
Country/Territory	Jamaica
City	Montego Bay
Period	24/07/19 → 26/07/19

Bibliographical note

Publisher Copyright:
© 2019 Latin American and Caribbean Consortium of Engineering Institutions. All rights reserved.

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10.18687/LACCEI2019.1.1.371

Cite this

Zapata-Quentasi, S., Yauri-Ituccayasi, A., Huamani-Avendaño, R., & Sulla Torres, J. A. (2019). Predicción para el negocio de alquiler de automóviles con técnicas supervisadas. In 17th LACCEI International Multi-Conference for Engineering, Education, and Technology: "Industry, Innovation, and Infrastructure for Sustainable Cities and Communities", LACCEI 2019 (Proceedings of the LACCEI international Multi-conference for Engineering, Education and Technology; Vol. 2019-July). Latin American and Caribbean Consortium of Engineering Institutions. https://doi.org/10.18687/LACCEI2019.1.1.371

Zapata-Quentasi, Sandra ; Yauri-Ituccayasi, Alba ; Huamani-Avendaño, Rodrigo et al. / Predicción para el negocio de alquiler de automóviles con técnicas supervisadas. 17th LACCEI International Multi-Conference for Engineering, Education, and Technology: "Industry, Innovation, and Infrastructure for Sustainable Cities and Communities", LACCEI 2019. Latin American and Caribbean Consortium of Engineering Institutions, 2019. (Proceedings of the LACCEI international Multi-conference for Engineering, Education and Technology).

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abstract = "Car rental is a new trend and is already a reality in many countries, as it is a cheaper option than maintaining your own. The objective of this article is to identify the ideal car for a person, according to the characteristics that you want. In the present work, a study was made of the previous steps involved in the prediction of a car according to the desired characteristics and a comparison of the classification algorithms was carried out to determine which classification is appropriate in terms of the accuracy of the prediction. The steps followed were: Data collection, preprocessing, data preparation and comparison of classification algorithms. The results obtained show that the Random Forest algorithm presents a 95.12% correct classification of the instances and a mean square error of 0.12, which are acceptable results for the tests performed.",

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year = "2019",

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Zapata-Quentasi, S, Yauri-Ituccayasi, A, Huamani-Avendaño, R & Sulla Torres, JA 2019, Predicción para el negocio de alquiler de automóviles con técnicas supervisadas. in 17th LACCEI International Multi-Conference for Engineering, Education, and Technology: "Industry, Innovation, and Infrastructure for Sustainable Cities and Communities", LACCEI 2019. Proceedings of the LACCEI international Multi-conference for Engineering, Education and Technology, vol. 2019-July, Latin American and Caribbean Consortium of Engineering Institutions, 17th LACCEI International Multi-Conference for Engineering, Education, and Technology, LACCEI 2019, Montego Bay, Jamaica, 24/07/19. https://doi.org/10.18687/LACCEI2019.1.1.371

Predicción para el negocio de alquiler de automóviles con técnicas supervisadas. / Zapata-Quentasi, Sandra; Yauri-Ituccayasi, Alba; Huamani-Avendaño, Rodrigo et al.

17th LACCEI International Multi-Conference for Engineering, Education, and Technology: "Industry, Innovation, and Infrastructure for Sustainable Cities and Communities", LACCEI 2019. Latin American and Caribbean Consortium of Engineering Institutions, 2019. (Proceedings of the LACCEI international Multi-conference for Engineering, Education and Technology; Vol. 2019-July).

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

TY - GEN

T1 - Predicción para el negocio de alquiler de automóviles con técnicas supervisadas

AU - Zapata-Quentasi, Sandra

AU - Yauri-Ituccayasi, Alba

AU - Huamani-Avendaño, Rodrigo

AU - Sulla Torres, Jose Alfredo

PY - 2019

Y1 - 2019

N2 - Car rental is a new trend and is already a reality in many countries, as it is a cheaper option than maintaining your own. The objective of this article is to identify the ideal car for a person, according to the characteristics that you want. In the present work, a study was made of the previous steps involved in the prediction of a car according to the desired characteristics and a comparison of the classification algorithms was carried out to determine which classification is appropriate in terms of the accuracy of the prediction. The steps followed were: Data collection, preprocessing, data preparation and comparison of classification algorithms. The results obtained show that the Random Forest algorithm presents a 95.12% correct classification of the instances and a mean square error of 0.12, which are acceptable results for the tests performed.

AB - Car rental is a new trend and is already a reality in many countries, as it is a cheaper option than maintaining your own. The objective of this article is to identify the ideal car for a person, according to the characteristics that you want. In the present work, a study was made of the previous steps involved in the prediction of a car according to the desired characteristics and a comparison of the classification algorithms was carried out to determine which classification is appropriate in terms of the accuracy of the prediction. The steps followed were: Data collection, preprocessing, data preparation and comparison of classification algorithms. The results obtained show that the Random Forest algorithm presents a 95.12% correct classification of the instances and a mean square error of 0.12, which are acceptable results for the tests performed.

KW - Car rental

KW - KDD

KW - Prediction

KW - Supervised techniques

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AN - SCOPUS:85073617254

T3 - Proceedings of the LACCEI international Multi-conference for Engineering, Education and Technology

BT - 17th LACCEI International Multi-Conference for Engineering, Education, and Technology

PB - Latin American and Caribbean Consortium of Engineering Institutions

Y2 - 24 July 2019 through 26 July 2019

ER -

Zapata-Quentasi S, Yauri-Ituccayasi A, Huamani-Avendaño R, Sulla Torres JA. Predicción para el negocio de alquiler de automóviles con técnicas supervisadas. In 17th LACCEI International Multi-Conference for Engineering, Education, and Technology: "Industry, Innovation, and Infrastructure for Sustainable Cities and Communities", LACCEI 2019. Latin American and Caribbean Consortium of Engineering Institutions. 2019. (Proceedings of the LACCEI international Multi-conference for Engineering, Education and Technology). doi: 10.18687/LACCEI2019.1.1.371

Predicción para el negocio de alquiler de automóviles con técnicas supervisadas

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