Open AccessSport-utility vehicle prediction based on machine learning approach
Author(s) -
G. Geetharamani,
K. Dhinakaran,
Janarthanan Selvaraj,
Savitoj Singh
Publication year - 2021
Publication title -
journal of applied research and technology
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.364
H-Index - 30
ISSN - 2448-6736
DOI - 10.22201/icat.24486736e.2021.19.3.1683
Subject(s) - purchasing , categorical variable , salary , logistic regression , computer science , software deployment , field (mathematics) , machine learning , artificial intelligence , marketing , operations research , data science , engineering , business , mathematics , economics , pure mathematics , market economy , operating system
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.