A PCA is primarily used for ______.

A. binary classification
B. dimension reduction
C. clustering

Correct Answer: B

PCA is a dimensionality reduction technique used to transform high-dimensional data sets into data sets with fewer dimensions consequently clarifying the structure of complex data sets. The set of resulting variables explains the maximum variance within the data sets which is difficult to visualize. The PCA process ensures the there is a minimum loss of information.