試題詳解

16. In dimensionality reduction, what is the main goal of Principal Component Analysis (PCA)?
(A) To increase the number of features in the dataset.
(B) To remove outliers from the dataset.
(C) To improve accuracy by adding new synthetic features.
(D) To transform correlated variables into uncorrelated ones while preserving variance.

(E) To cluster similar data points together.