Package: Spectrum
Title: Versatile Ultra-Fast Spectral Clustering for Single and
        Multi-View Data
Version: 0.3
Author: Christopher R John, David Watson
Maintainer: Christopher R John <chris.r.john86@gmail.com>
Description: A versatile ultra-fast spectral clustering method for single or multi-view data. 'Spectrum' uses a new type of adaptive density aware kernel that strengthens local connections in dense regions in the graph. For integrating multi-view data and reducing noise we use a recently developed tensor product graph data integration and diffusion system. 'Spectrum' contains two techniques for finding the number of clusters (K); the classical eigengap method and a novel multimodality gap procedure. The multimodality gap analyses the distribution of the eigenvectors of the graph Laplacian to decide K and tune the kernel. 'Spectrum' is suited for clustering a wide range of complex data.
Depends: R (>= 3.5.0)
License: AGPL-3
Encoding: UTF-8
LazyData: true
Imports: ggplot2, Rtsne, ClusterR, umap, Rfast, RColorBrewer, diptest
Suggests: knitr
VignetteBuilder: knitr
RoxygenNote: 6.1.1
NeedsCompilation: no
Packaged: 2019-02-15 14:39:19 UTC; christopher
Repository: CRAN
Date/Publication: 2019-02-18 10:00:18 UTC
