Which is the best-fit definition for the use of Principal Component Analysis (PCA)?
A) The elimination of the number of components in a data set to identify errors.
B) The transformation of a small set of correlated variables into larger uncorrelated subsets.
C) The transformation of a large number of correlated variables into a smaller number of uncorrelated variables.
D) The driving of pattern recognition in a supervised data mining set used to visualize data methods.

Question

Quizplus · Accepted Answer

Principal Component Analysis (PCA) is primarily used for dimensionality reduction in data sets, transforming a large number of correlated variables into a smaller number of uncorrelated variables. This helps in simplifying the data without losing much information.

Which Is the Best-Fit Definition for the Use of Principal