… classifier approach is not reliable for prediction of car prices. Therefore, in … car prices
prediction was proposed. To apply ensemble of machine learning classifiers a new attribute “price …

… Using the Scikit learn library in python, we build the KNN (k = 7) and CART models for
predicting the value of a vehicle. The value for the desired k was not directly decided rather we try …

… car to estimate the pricing value of the used car they are willing to buy or sell, we build a
machine learning model to predict the car price … , fuel type, fiscal power, car mark, and its model. …

… The model will reliably forecast the price of cars by selecting … car price occupancy rate
prediction based on Deep Learning … of automatically designing a deep network that encapsulates …

… The primary goal of this study is to develop a deep-learning framework to predict car prices.
We explored basic regression techniques like linear regression, tree-based regression, …

… Section III describes the methodology while in section IV, we describe, evaluate and compare
different machine learning techniques to predict the price of used cars. Finally, we end the …

… Machine Learning algorithms can be used to predict the retail … The main objective of this
paper is to use three different prediction models to predict the retail price of a used car and …

… model that can predict a used vehicle's price using machine learning. With this model, vehicle
purchasers will determine a particular used car's reasonable price given certain conditions…

… Due to the large growth in the number of cars being bought and sold, used-car price
prediction creates a lot of interest in analysis and research. The availability of used …

… model using machine learning algorithms to determine the approximate value of a used car.
… [5] proposed a vehicle price prediction system using machine learning techniques. Another …