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|
|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|
|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
|Name||Proceedings of the LACCEI international Multi-conference for Engineering, Education and Technology|
|Conference||17th LACCEI International Multi-Conference for Engineering, Education, and Technology, LACCEI 2019|
|Period||24/07/19 → 26/07/19|
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