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  3. Winning a Kaggle Competition in Python

Exercise

Model blending

You will start creating model ensembles with a blending technique.

Your goal is to train 2 different models on the New York City Taxi competition data. Make predictions on the test data and then blend them using a simple arithmetic mean.

The train and test DataFrames are already available in your workspace. features is a list of columns to be used for training and it is also available in your workspace. The target variable name is "fare_amount".

Instructions

100 XP
  • Train a Gradient Boosting model on the train data using features list, and the "fare_amount" column as a target variable.
  • Train a Random Forest model in the same manner.
  • Make predictions on the test data using both Gradient Boosting and Random Forest models.
  • Find the average of both models predictions.