Resumen

GEETHARAMANI, G.; DHINAKARAN, K.; SELVARAJ, Janarthanan  y  SINGH, S. Christopher Ezhil. Sport-utility vehicle prediction based on machine learning approach. J. appl. res. technol [online]. 2021, vol.19, n.3, pp.184-193.  Epub 01-Oct-2021. ISSN 2448-6736.  https://doi.org/10.22201/icat.24486736e.2021.19.3.1683.

Data mining and machine learning analytics in manufacturing field is one of the major research fields in Information Technology with a lot of challenges. The goal of this research is to design a categorical solution to decide whether a customer is eligible and interested to purchase a sport-utility vehicle (SUV) based on the available data from the previous records collected from the banks. The data from different customers across various ages who have purchased the sport-utility vehicle earlier are collected and used in building a solution for this logistic model. A range of age and an estimated salary across different ages are the dependent factors in building this model. In addition, this model will predict the binary logistic outcome to show whether a customer can purchase a sport-utility vehicle or not. By enhanced cloud platform with larger volume of data keeping the algorithm remains the same using machine learning deployment for predicting the customer mindset in purchasing a sport-utility vehicle.

Palabras llave : Data mining; machine learning; prediction; classification; logistic regression; scikit-learn.

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