r-spectrum 1.1 Fast adaptive spectral clustering for single and multi-view data

This package provides a self-tuning spectral clustering method for single or multi-view data. Spectrum uses a new type of adaptive density aware kernel that strengthens connections in the graph based on common nearest neighbours. It uses a tensor product graph data integration and diffusion procedure to integrate different data sources and reduce noise. Spectrum uses either the eigengap or multimodality gap heuristics to determine the number of clusters. The method is sufficiently flexible so that a wide range of Gaussian and non-Gaussian structures can be clustered with automatic selection of K.