PCA is one of the most popular and widely used linear dimensionality reduction methods. Sometimes it is used alone and sometimes as a starting solution for other dimensionality reduction algorithms. PCA is a projection based methods which transforms the data by projecting in onto another set of orthogonal axes. It provides a closed form solution for the problem. PCA is simple and easy to understand unlike some other complex algorithms which work as black box.
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