Reading 17: Density Estimation and Clustering

Reading 17: Density Estimation and Clustering#

For the class on Monday, April 7th

Reading assignments#

Read the following sections of [The20]:

  • Sec. 1.6 “Unsupervised and Semisupervised Learning”

  • Sec. 12.6 “Gaussian Mixture Models”

    • Skip the derivation from Eq. (12.55) to Eq. (12.62).

    • Read “Remarks 12.4”.

  • Sec. 12.6.1 “Gaussian Mixture Modeling and Clustering”

Questions#

Submit your answer on Canvas. Due at noon, Monday, April 7th.

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. Mixture modeling is a popular technique for density estimation and clustering. These two tasks are closely related.

    • In the context of clustering, whose density does mixture modeling try to estimate? (i.e., the density of which variable(s) is being estimated?)

    • After approximating the density with mixture models, how are the clusters assigned?