I am trying to create a regression model using scikit-learn for predicting car price. The input data are, car model(trim), kilometers used, past resale price of similar car and age of used car. I am trying to predict the future resale price of the car.
I have done the preprocessing of data. I have tried using ARDRegression, RandomForestRegressor and finally MLPRegressor. But the prediction model doesn't seem to predict well, the prediction results seem to fall outside the range of training data.
Example: if the Actual value(actual selling price) is 748077.0 but predicted value is 1352960
Probably I have done some mistake but I am not able to figure out what it is. I have simplified the code to focus on prediction part and have shared the link.
Could someone please guide me.
Update: Inverting the index of the dataframe iresults in total change of prediction.