Principal Component Analysis is a technique that helps to find out the most common dimensions of the dataset and makes result analysis simpler.
In the available dataset not all these datasets dimension is critical, some may be the primary key datasets, whereas others are not.
So, PCA Method of factor analysis gives a calculative way of eliminating a few extra less important variables, thereby maintaining the transparency of all information.
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