A fast, accurate, and modularized dimensionality reduction approach based on diffusion harmonics and graph layouts. Escalates to millions of samples on a personal laptop. Adds high-dimensional big data intrinsic structure to your clustering and data visualization workflow.
Implements fast neighbor search via NMSlib;
Implements classes and improvements for a fast and scalable diffusion process;
Implements a faster UMAP adaptation;
Implements graph utilities for building graphs with dbMAP;
Implements plotting utility.
First public release of the algorithm.