This is an implementation of the
largeVis algorithm described in (https://arxiv.org/abs/1602.00370). It also incorporates:
- A very fast algorithm for estimating k-nearest neighbors, implemented in C++ with
OpenMP. See the Benchmarks file for performance details.
- Efficient implementations of the clustering algorithms:
- Functions for visualizing manifolds like this.
- Version 0.1.10 re-adds clustering, and also adds momentum training to largeVis, as well as a host of other features and improvements.
- Version 0.1.9.1 has been accepted by CRAN. Much grattitude to Uwe Ligges and Kurt Hornik for their assistance, advice, and patience.
Clustering With HDBSCAN
- Note on R 3.4: Before R 3.4, the CRAN binaries were likely to have been compiled without OpenMP, and getting OpenMP to work on Mac OS X was somewhat tricky. This should all have changed (for the better) with R 3.4, which natively using
clang 4.0by default. Since R 3.4 is new, I'm not able to provide advice, but am interested in hearing of any issues and any workarounds to issues that you may discover.