rogers_tanimoto: Computes the Rogers-Tanimoto similarity of two clusterings of...

Description Usage Arguments Details Value Examples

View source: R/similarity.r

Description

For two clusterings of the same data set, this function calculates the Rogers-Tanimoto similarity coefficient of the clusterings from the comemberships of the observations. Basically, the comembership is defined as the pairs of observations that are clustered together.

Usage

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rogers_tanimoto(labels1, labels2)

Arguments

labels1

a vector of n clustering labels

labels2

a vector of n clustering labels

Details

To calculate the Rogers-Tanimoto similarity, we compute the 2x2 contingency table, consisting of the following four cells:

n_11:

the number of observation pairs where both observations are comembers in both clusterings

n_10:

the number of observation pairs where the observations are comembers in the first clustering but not the second

n_01:

the number of observation pairs where the observations are comembers in the second clustering but not the first

n_00:

the number of observation pairs where neither pair are comembers in either clustering

The Rogers-Tanimoto similarity is defined as:

\frac{n_{11} + n_{00}}{n_{11} + 2 (n_{10} + n_{01}) + n_{00}}.

To compute the contingency table, we use the comembership_table function.

Value

the Rogers-Tanimoto index for the two sets of cluster labels

Examples

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## Not run: 
# We generate K = 3 labels for each of n = 10 observations and compute the
# Rogers-Tanimoto similarity coefficient between the two clusterings.
set.seed(42)
K <- 3
n <- 10
labels1 <- sample.int(K, n, replace = TRUE)
labels2 <- sample.int(K, n, replace = TRUE)
rogers_tanimoto(labels1, labels2)

# Here, we cluster the \code{\link{iris}} data set with the K-means and
# hierarchical algorithms using the true number of clusters, K = 3.
# Then, we compute the Rogers-Tanimoto similarity index between the two
# clusterings.
iris_kmeans <- kmeans(iris[, -5], centers = 3)$cluster
iris_hclust <- cutree(hclust(dist(iris[, -5])), k = 3)
rogers_tanimoto(iris_kmeans, iris_hclust)

## End(Not run)

ramhiser/clusteval documentation built on Oct. 17, 2017, 12:26 p.m.