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The purpose of this example is to compare the performance of machine learning models within a Jupyter notebook. We will use the classic 1974 Motor Trend car road tests () dataset to fit and evaluate three models:

  1. A linear model using all variables
  2. A linear model after variable selection
  3. A Gradient Boosting Machine (GBM) model 

The notebooks below are modified versions of a Python notebook originally created by a Microsoft employee for distribution on the Cortana Intelligence Gallery.

Modified on: Jul 12, 2019
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