## What is the difference between Multi-Dimensional Scaling and Principal Component Analysis?

**Principal Component Analysis**

The input to PCA is the original vectors in n-dimensional space.

And the data are projected onto the directions in the data with the most variance. Hence the “spread” of the data is roughly conserved as the dimensionality decreases.

**Multidimensional Scaling**

The input to MDS is the pairwise distances between points.

The output of MDS is a two- or three-dimensional projection of the points where distances are preserved.

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