Reading 12: Supervised: Regression I#
For the class on Wednesday, March 5th
Reading assignments#
Read the following sections of [The20]:
Sec. 3.2 “Parameter Estimation: the Deterministic Point of View”
Sec. 3.3 “Linear Regression”
Sec. 3.8 “Regularization”
Including the “Inverse Problems: Ill-Conditioning and Overfitting” subsection
Hint
Acronyms: LS = least-squares. MVU = Minimum-variance unbiased (defined in Sec. 3.6 but you don’t need the details for reading Sec. 3.8).
Questions#
Submit your answer on Canvas. Due at noon, Wednesday, March 5th.
Warning
If you use AI to help answer the following questions, make sure you read and agree with what it says!
List anything from your reading that confuses you. Explain why they confuse you. If nothing confuses you, briefly summarize what you have learned from this reading assignment.
Use your own words to (briefly) define linear regression.
Can you use linear regression to fit a parabola to a set of data points? Why or why not.