What is the main objective of PCA?

Subject: Machine Learning

Topic: Statistical Learning and Feature Engineering

Options:

1. Option A: To increase the number of features.
2. Option B: To create a new set of uncorrelated features that capture maximum variance.
3. Option C: To cluster similar data points together.
4. Option D: To find association rules between items.

Correct Answer:

Option B: To create a new set of uncorrelated features that capture maximum variance.

Explanation:

PCA aims to transform the original features into a new set of orthogonal (uncorrelated) features called principal components, ordered by the amount of variance they capture from the data.