A car price prediction model predictor and analyzer with visualization tools and amazing results on dataset.

[Rohit-Sharma-RS]

Model Training

We explore multiple regression models to identify the best-performing one:

• Random Forest Regressor
• Gradient Boosting Regressor
• XGBoost Regressor

For each model, we evaluate performance using error metrics such as MAE, MSE, RMSE, and R² Score.

Model Evaluation

We compare the performance of all trained models based on the calculated error metrics.

Summary of Results

Almost 95% on test set and 99.6 percent on train set. After evaluating all models, we identify XGBoost as the best performer based on:

• Lowest Test MAE
• Lowest Test RMSE
• Highest Test R² Score

[Rohit-Sharma-RS]

@MohammedHamzaMalik for issue #7

[MohammedHamzaMalik]

Looks good!