Feature Engineering and Feature Selection Using the Automobile Dataset

This video presents my feature engineering and feature selection analysis using the Automobile Dataset. I explore the dataset using descriptive statistics, histograms, box plots, outlier detection, and correlation analysis. I then create three new features and compare a baseline Random Forest model with a model using the engineered features. I also apply multiple feature selection techniques and compare model performance using MAE, RMSE, and R². Finally, I discuss the results and how feature engineering and feature selection affected the model’s ability to predict automobile prices.