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CS 4320: Machine Learning

Assignment : Linear Regression

In this assignment, you will use linear regression to fit a model to a collection of data. Your goal is to minimize the MSE on a set of test data.

Use your personal data set available on Canvas in the regression-1 folder.

Explore and analyze this data as you did in the previous assignment. Include the plots and analysis in your report.

Fit a linear regression model to the data. Note this means find the parameters.

It is expected that you will use the sklearn.linear_model.SGDRegressor to find the best model.

You will need to record the MSE found on the training data, and the MSE found on the testing data.

Required Steps

• Download your data.
• Explore and analyze your data.
• Split the data 80%/20%, for training/testing.
• Write (or modify) a Python program using sklearn to fit the training data to a SGDRegressor model.
• Report the MSE loss obtained for your best model on the training data.
• Report the MSE loss obtained for your best model on the testing data.
• Report the linear model coefficients found.
• Report your model function.
• Commit and push your code in the git repository.
• Submit the report (as PDF) to Canvas.

Last Updated 01/16/2023