This repo serves for the usage of linear regressions in datasets that vary in decision making for housing and finances.

Please change the name of the path directories in which the data and the models can be saved. This are the variables named "path#". The docs should be found in a local directory called docs.

Please install libraries required for the Python program to run. In case there is a problem, a google colab link has been provided inside the code for usage online. It is linked to an open drive that contains the data used for the analysis. Would require a google account to access it but is open to anyone.

function reader = reads data from txt files.

function boston_split = serves for splitting datasets for boston housing info.

function optim_ridge = solution function for ridge regression of the boston housing data.

function optim_lasso = solution function for lasso regression of the boston housing data.

function optim_ridge_e20 = solution function for ridge regression of e2006 data.

function optim_lasso_e20 = solution function for lasso regression of e2006 data.

function ridge_model = creates a ridge model with varying alpha.

function lasso_model = creates a lasso model with varying alpha.

function e2006_split = splits data from e2006 dataset.

function coeff_matrices = creates matrices with interceptions, RMSE and the correlated variables.

function plot_rmse = plots RMSE curves.

function ridge_kfold = performs 5-cross validation analysis on ridge regression.

function lasso_kfold = performs 5-cross validation analysis on lasso regression.