Auto Acquired Vehicle Valuation Model
This repository contains the final trained Random Forest model used by the
Machine Learning Vehicle Valuation and Negotiation Support System.
Model File
random_forest_model.joblib
Installation
Download the model file and save it at:
C964_Capstone/models/random_forest_model.joblib
The filename must remain exactly:
random_forest_model.joblib
After placing the file in the models folder, open a terminal in the main
C964_Capstone folder and run:
python main.py
The downloaded model allows menu option 1 to generate vehicle-value predictions
without retraining the Random Forest model.
Model Details
- Model type: Random Forest Regressor
- Prediction target:
sellingprice
- Number of estimators: 100
- Train-test split: 80/20
- Random state: 42
- Model version: 1.0
Only load this joblib file if it was downloaded from this official project
repository.
