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Predicción para el Negocio de Alquiler de Automóviles con Técnicas Supervisadas | ||
| Published in: | Industry, Innovation, and Infrastructure for Sustainable Cities and Communities: Proceedings of the 17th LACCEI International Multi-Conference for Engineering, Education and Technology |  |
| Date of Conference: | July 24-26, 2019 | |
| Location of Conference: | Montego Bay, Jamaica | |
| Authors: | Sandra Zapata-Quentasi (Universidad Nacional de San Agustín de Arequipa, PE) Alba Yauri-Ituccayasi (Universidad Nacional de San Agustín de Arequipa, PE) Rodrigo Huamani-Avendaño (Universidad Nacional de San Agustín de Arequipa, PE) Jose Sulla-Torres (Universidad Nacional de San Agustín de Arequipa, PE) (Universidad Nacional de San Agustín de Arequipa) | |
| Full Paper: | #371 | |
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. | ||