clusterStability: Cluster Stability. J = \frac{n_{11}}{n_{11} + n_{10} +...

In nguforche/UnsupRF: Unsupervised Random Forest Clustering

J = \frac{n_{11}}{n_{11} + n_{10} + n_{01}}

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Description

Computes the cluster stability measure defined in Famili et.al based on the idea of cluster immovability on partition. Cluster immovability is the rate at which the content of a cluster remains unchanged during the clustering process.

Usage

Stability(c1, c2)

Arguments

c1	a vector of n clustering labels
c2	a vector of n clustering labels

Value

the Jaccard coefficient for the two sets of cluster labels (See Details.)

References

Famili, A. Fazel, Ganming Liu, and Ziying Liu. "Evaluation and optimization of clustering in gene expression data analysis." Bioinformatics 20.10 (2004): 1535-1545.

Examples

## Not run: 
# We generate K = 3 labels for each of n = 10 observations and compute the
# Jaccard 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)
jaccard_indep(labels1, labels2)

# Here, we cluster the iris data set with the K-means and
# hierarchical algorithms using the true number of clusters, K = 3.
# Then, we compute the Jaccard similarity coefficient between the two
# clusterings.
iris_kmeans <- kmeans(iris[, -5], centers = 3)$cluster
iris_hclust <- cutree(hclust(dist(iris[, -5])), k = 3)
jaccard_indep(iris_kmeans, iris_hclust)

## End(Not run)

nguforche/UnsupRF documentation built on May 5, 2019, 4:51 p.m.