What is the primary purpose of Principal Component Analysis (PCA)?

To calculate the mean of data
To classify data
To reduce dimensionality of data
To visualize data

The primary purpose of PCA is to reduce the dimensionality of data while maintaining as much information as possible. It transforms the data into a new, lower-dimensional set of variables that are uncorrelated and that explain the maximum possible amount of variance in the data.

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