Multiple linear regression model to predict house prices.
This project is based on the Dataquest mission 240 guided project where feature selection and feature engineering is used to train and test a multiple linear regression model to predict house sale prices. The regression model is trained on data for houses sold in the city of Ames, Iowa. This project expands on the guided project by implementing parameter optimization to find the optimal number of k-folds when using k-fold cross validation to measure the regression model's accuracy. With our regression model and optimal number of k-folds for cross validation, our alogrithm can be used to predict the sale price for houses in the city of Ames, Iowa.