THE DATASET IS REGARDING THE VEHICLES WHICH ARE BEING PRICED AFTER A GIVEN TIME PERIOD (cars.csv)
It consists of the information of the used cars from www.cardekho.com
The following data can be divided in the following categories:
- Introduction
- Loading Data and Explanation of features
- Exploratory data analysis
- Applying regression models
- Conclusion
This projects main motive is to predict out the price of the used cars with the help of various regression models.
INDEPENDENT VARIABLES TO BE USED IN THE DATASET ARE:
1.Car_Name: Denotes the vehicle name with the model in the dataset
2.Year : the year in shich the vehicle is being taken
3.Selling_Price: The selling price of the vehicle
4.Present_Price : The price at the present stage
5.Kms_Driven : Amount of kilometres traversed by the vehicle
6.Fuel_Type : To determine whether the fuel used in the vehicle is petrol,diesel or CNG
7.Seller_Type : The type of manufacturere, i.e, the person from whom the vehicle is purchased
8.Transmission : It has only two options , either manually transmitted or automatic transmitted
9.Owner : The number of owners to determine the vehicle is first hand , second hand or anything else.
Various regression models are also being used in this case : a.Linear Regression b.Lasso c.Ridge d.Decision Tree Regressor e.Random Forest Regressor
The results are being taken and analysed and thus this results in the comparision of various models in the price prediction of the vehicles in the dataset.