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

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-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 contributionPrediction for the car rental business with supervised techniques
Original languageSpanish
Title of host publication17th LACCEI International Multi-Conference for Engineering, Education, and Technology
Subtitle of host publication"Industry, Innovation, and Infrastructure for Sustainable Cities and Communities", LACCEI 2019
PublisherLatin American and Caribbean Consortium of Engineering Institutions
ISBN (Electronic)9780999344361
DOIs
StatePublished - 2019
Event17th LACCEI International Multi-Conference for Engineering, Education, and Technology, LACCEI 2019 - Montego Bay, Jamaica
Duration: 24 Jul 201926 Jul 2019

Publication series

NameProceedings of the LACCEI international Multi-conference for Engineering, Education and Technology
Volume2019-July
ISSN (Electronic)2414-6390

Conference

Conference17th LACCEI International Multi-Conference for Engineering, Education, and Technology, LACCEI 2019
Country/TerritoryJamaica
CityMontego Bay
Period24/07/1926/07/19

Bibliographical note

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

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