Wolfram Language

Learn a Nonlinear Manifold on Numeric Data

DimensionReduction learns a parametrized manifold on which most of the data lies. In this example, learn and visualize the manifold of three-dimensional data.

Generate a "Swiss roll" dataset.

Train a nonlinear dimension reducer on the dataset. The dimension is reduced from 3 to 2.

The inverse reduction can be interpreted as a parametric surface. Visualize this surface by generating (u, v) points and transforming them with the inverse reduction .

Now visualize the dataset in the original space, with each point colored according to its reduced variable u.

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