Python code snippets to perform the following task:
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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.
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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
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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.