integrate_similarity_matrices: integrate_similarity_matrices: integrate similarity matrices...

In Spectrum: Fast Adaptive Spectral Clustering for Single and Multi-View Data

Description

Given a list of similarity matrices this function will integrate them running the Shu algorithm, also can reduce noise if the input is a list consisting of a single matrix.

Usage

integrate_similarity_matrices(kernellist, KNNs_p = 10,
  diffusion_iters = 4, method = "TPG")

Arguments

kernellist	A list of similarity matrices: those to be integrated
KNNs_p	Numerical value: number of nearest neighbours for KNN graph (default=10, suggested=10-20)
diffusion_iters	Numerical value: number of iterations for graph diffusion (default=4, suggested=2-6)
method	Character: either TPG (see reference below) or mean (default=TPG)

Value

An integrated similarity matrix

References

Shu, Le, and Longin Jan Latecki. "Integration of single-view graphs with diffusion of tensor product graphs for multi-view spectral clustering." Asian Conference on Machine Learning. 2016.

Examples

i_test <- integrate_similarity_matrices(misslfilled,method='mean')

Spectrum documentation built on Feb. 10, 2020, 9:07 a.m.