CE_MLBM-proc: CE_MLBM function for agreement between co-clustering...

In bikm1: Co-Clustering Adjusted Rand Index and Bikm1 Procedure for Contingency and Binary Data-Sets

Description

Produce a measure of agreement between two triplets of partitions for co-clustering. A value of 1 means a perfect match.

Usage

CE_MLBM(z,v,w,zprime,vprime,wprime)

Arguments

z	numeric vector specifying the class of rows.
v	numeric vector specifying the class of column partitions for the first matrix.
w	numeric vector specifying the class of column partitions for the second matrix.
zprime	numeric vector specifying another partitions of rows.
vprime	numeric vector specifying another partition of columns for the first matrix.
wprime	numeric vector specifying another partition of columns for the second matrix.

Value

the value of the index (between 0 and 1). A value of 0 corresponds to a perfect match.

Examples

require(bikm1)
set.seed(42)
n=200
J=120
K=120
g=2
h=2
l=2
theta=list()
theta$pi_g=1/g *matrix(1,g,1)
theta$rho_h=1/h *matrix(1,h,1)
theta$tau_l=1/l *matrix(1,l,1)
theta$alpha_gh=matrix(runif(4),ncol=h)
theta$beta_gl=matrix(runif(4),ncol=l)
data=BinBlocRnd_MLBM(n,J,K,theta)
res=BIKM1_MLBM_Binary(data$x,data$y,2,2,2,4,init_choice='smallVBayes')
error=CE_MLBM(res@model_max$z,res@model_max$v,res@model_max$w,data$xrow,data$xcolx,data$xcoly)

bikm1 documentation built on July 16, 2021, 9:08 a.m.