# NOT RUN {
# 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)
# }
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