misClustRate: Mis-Classification Rate (MCR)
In epca: Exploratory Principal Component Analysis
misClustRate R Documentation
Mis-Classification Rate (MCR)
Description
Compute the empirical MCR, assuming that #cluster = #block,
This calculation allows a permutation on clusters.
Usage
misClustRate(cluster, truth)
Arguments
cluster
vector of integer or factor, estimated cluster membership.
truth
a vector of the same length as clusters, the true cluster labels.
Value
numeric, the MCR.
Examples
truth = rep(1:3, each = 30)
cluster = rep(3:1, times = c(25, 32, 33))
misClustRate(cluster, truth)
epca documentation built on July 26, 2023, 5:47 p.m.
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| misClustRate | R Documentation |
Mis-Classification Rate (MCR)
Description
Compute the empirical MCR, assuming that #cluster = #block, This calculation allows a permutation on clusters.
Usage
misClustRate(cluster, truth)
Arguments
cluster |
vector of |
truth |
a vector of the same length as |
Value
numeric, the MCR.
Examples
truth = rep(1:3, each = 30)
cluster = rep(3:1, times = c(25, 32, 33))
misClustRate(cluster, truth)
R Package Documentation
Browse R Packages
We want your feedback!
Note that we can't provide technical support on individual packages. You should contact the package authors for that.
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