Open AccessObject detection and used car price predicting analysis system (UCPAS) using machine learning technique
Author(s) -
Anoop Yadav,
Ela Kumar,
Piyush Kumar Yadav
Publication year - 2021
Publication title -
linguistics and culture review
Language(s) - English
Resource type - Journals
ISSN - 2690-103X
DOI - 10.21744/lingcure.v5ns2.1660
Subject(s) - machine learning , computer science , artificial intelligence , outcome (game theory) , random forest , object (grammar) , task (project management) , object detection , cluster analysis , support vector machine , contrast (vision) , pattern recognition (psychology) , engineering , mathematics , mathematical economics , systems engineering
The highly interesting research area that noticed in the last few years is object detection and find out the prediction based on the features that can be benefited to consumers and the industry. In this paper, we understand the concept of object detection like the car detection, to look into the price of a second-hand car using automatic machine learning methods. We also understand the concept of object detection categories. Nowadays, the most challenging task is to determine what is the listed price of a used car on the market, Possibility of various factors that can drive a used car price. The main objective of this paper is to develop machine learning models which make it possible to accurately predict the price of a second-hand car according to its parameter or characteristics. In this paper, implementation techniques and evaluation methods are used on a Car dataset consisting of the selling prices of various models of car across different cities of India. The outcome of this experiment shows that clustering with linear regression and Random Forest model yield the best accuracy outcome. The machine learning model produces a satisfactory result within a short duration of time compared to the aforementioned self.