Machine Learning, Tutorial, Dimensionality Reduction, Deep Learning, Python.
axes (principal components) of the new subspace can be interpreted as the directions of maximum variance given the constraint that the new feature axes are orthogonal to each other, as illustrated in the following figure: In the preceding figure, x1 and x2 are the original feature axes, and PC1 and