high dimensionality

What Is PCA Research? Principal component analysis (PCA) is a technique for reducing the dimensionality of such datasets, increasing interpretability but at the same time minimizing information loss. It does so by creating new uncorrelated variables that successively maximize variance. What is PCA and when it is used? PCA is the mother method for MVDA