Boston Home Prices Machine Learning Analysis 🏠

This project examines the key factors influencing Boston home prices using machine learning models (KNN algorithm, step-wise regression, random forest). The goal is to understand which factors drive median home values (medv) and to identify the best predictive model. We have 13 predictor variables to work with which can result in a large number of possible models. In this project, we will use a model with all 13 predictors (model 1), a model derived by analyzing correlations and random forest (model 2), and a model selected using step-wise regression (model 3). Then we’ll measure the predictive accuracy of these models by creating training and test data sets, using the training data to predict the test data, and analyze the performance results.