Programming 5 - Linear Regression

Goal

• Learn to implement linear regression algorithms.

• Improve performance by handling interactive effects, fitting a nonlinear relationship, reducing variance with regularization, and reducing features with lasso regression.

Readings

• Chapter 13 Linear Regression,  Machine Learning with Python Cookbook 2nd,  Free O'Reilly Learning by FJU ID

Instructions

• Read the reading and practice all the Python codes.

• Exercise: Use the California housing dataset in Scikit-Learn real-world dataset. Modify the Python codes to perform linear regression on the California housing data. Analyze the results of output, explain the results, and improve the results.

Report: a separate and single web page that you

• • Write the goal of this assignment

  • Explain the linear regression algorithm. Explain the Scikit-Learn functions of linear regression.

  • Explain the Python codes. Upload code output results into your report web page. Explain the results of the output results

  • Clearly explain modified code segments written by you. Give some analysis in your report.

  • Give references to this assignment (teacher's readings, your readings)

Submit the web address of your web page to Microsoft Teams.