labelCluster: Label Cluster

In epca: Exploratory Principal Component Analysis

Label Cluster

Description

Assign cluster labels to each row from the membership matrix.

Usage

labelCluster(x, ties.method = "random")

Arguments

x	matrix with non-negative entries, where x[i,j] is the estimated likelihood (or any equivalent measure) of node i belongs to block j. The higher the more likely.
ties.method	character, how should ties be handled, "random", "first", "last" are allowed. See base::rank() for details.

Value

integer vector of the same length as x. Each entry is one of 1, 2, ..., ncol(x).

epca documentation built on July 26, 2023, 5:47 p.m.