Partial-Dependent-Plots-Individual-Conditional-Expectation-Plots

Python code snippets to perform the following task:

1. Modeling Training a simple Linear Regression model Training an advanced Gradient Boosting (XGBoost) Regression model Evaluating both models and comparing them on the Validation Root Mean Squared Error metric.

2. Partial Dependence Plots Generating the following PDPs (for both models): a) For predictor/feature "Mfg_Year", which is indicative of the 'Age' of a vehicle. b) For predictor/feature "HP", which is indicative of the (horse) power of the vehicle's engine. c) For predictor/feature "KM", it indicates the vehicle's (accumulated) Kilometers on the odometer

3. Individual Conditional Expectation Plots Generating ICE Plots (for both models) on the same predictors as above. The ICE Plots were generated for 10 unique points.