Simple Regression Ensemble Model for Boston Housing with Python

Credit: Template and study cases were adapted from blog posts made available by Dr. Jason Brownlee of Machine Learning Mastery.

For more information on this case study project, please consult Dr. Brownlee’s blog post at https://machinelearningmastery.com/regression-machine-learning-tutorial-weka/.

Dataset Used: Housing Values in Suburbs of Boston

ML Model: Regression, numeric inputs

Dataset Reference: https://archive.ics.uci.edu/ml/datasets/Housing

The purpose of this project is to analyze a dataset using various machine learning algorithms and to document the steps using a template. The project aims to touch on the following areas:

  1. Document a regression predictive modeling problem end-to-end.
  2. Explore feature selection options for improving model performance
  3. Explore algorithm tuning techniques for improving model performance

For this “Take-2” version of the project, we added the ensemble models to the exploration.

  1. Explore using and tuning ensemble methods for improving model performance

The HTML formatted report can be found here on GitHub.