[SOLVED] Homework 3 Statistics

Homework 3

This homework is worth a total of 100 points.

Each question is worth 20 points.

1. What are the main motivations for reducing a dataset’s dimensionality? What are the main drawbacks?

2. Suppose you perform. PCA on a 1,000-dimensional dataset, setting the explained variance ratio to 95%. How many dimensions will the resulting dataset have?

3. How can you evaluate the performance of a dimensionality reduction algorithm on your dataset?

4. How would you define clustering? Can you name a few clustering algorithms?

5. What are some of the main applications of clustering algorithms?