The Living Thing / Notebooks : Dimensionality reduction

Wherein I teach myself, amongst other things, how a sparse PCA works, and work out where to file multidimensional scaling.

Should I rename this to “feature construction”? Some of the same techniques, but we drop the assumption that we wish to decrease the number of dimensions. Or even “clustering“? The overlap is considerable.

See also matrix factorisations and random features, high-dimensional statistics and discuss random projections and their role in compressed sensing etc.

Special case: t-SNE