Reading 18: Dimensionality Reduction

Reading 18: Dimensionality Reduction#

For the class on Wednesday, April 9th

Reading assignments#

Read the following sections of [The20]:

  • Sec. 3.12 “Curse of Dimensionality”

  • Sec. 19.1 “Introduction”

  • Sec. 19.2 “Intrinsic Dimensionality”

  • Sec. 19.3 “Principal Component Analysis”

    • Skip the subsections (i.e., stop at the heading “PCA, SVD, AND LOW RANK MATRIX FACTORIZATION” on Page 1043).

    • Read “Remarks 19.1” on Page 1048.

Questions#

Submit your answer on Canvas. Due at noon, Wednesday, April 9th.

Warning

If you use AI to help answer the following questions, make sure you read and agree with what it says!

  1. 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.

  2. The PCA is a way to transform the input features.

    • What is the constraint on the transformation? (Can it be any possible transformation, or of only a certain kind?)

    • What does the transformation aim to achieve? (After the transformation, what does the first principal component correspond to?)