spectrumShift: Spectrum shift

In klic: Kernel Learning Integrative Clustering

Description

Make a symmetric matrix positive semi-definite.

Usage

spectrumShift(kernelMatrix, coeff = 1.2, shift = NULL, verbose = FALSE)

Arguments

kernelMatrix	symmetric matrix
coeff	Coefficient by which the minimum eigenvalue is multiplied when shifting the eigenvalues, in order to avoid numeric problems. Default is 1.2.
shift	Value of the constant added to the diagonal, if known a priori. Default is NULL.
verbose	Boolean flag: if TRUE, information about the shift is printed to screen. Default is FALSE.

Value

This function returns the matrix kernelMatrix after applying the required spectrum shift.

Author(s)

Alessandra Cabassi [e-mail]

Examples

# Load one dataset with 300 observations, 2 variables, 6 clusters
data <- as.matrix(read.csv(system.file("extdata", "dataset1.csv",
package = "klic"), row.names = 1))

# Compute consensus clustering with K=4 clusters
cm <- coca::consensusCluster(data, 4)

# Shift eigenvalues of the matrix by a constant: (min eigenvalue) * (coeff)
km <- spectrumShift(cm, coeff = 1.05)

klic documentation built on July 8, 2020, 6:23 p.m.