mediod: mediods of a clustering procedure

In nguforche/UnsupRF: Unsupervised Random Forest Clustering

Description

Calculate the mediods of a clustering by finding the point that has the minimum average/sum distance to all other points in the cluster. Proximity between data points can be provided by RFdist or using the Gower's general similarity coefficient.

Usage

mediod(x, ...)

## Default S3 method:
mediod(x, clusters, fun = "sum", weights, ...)

mix.dist(data, weights)

## S3 method for class 'mediod'
print(x, ...)

Arguments

x	a dissimilarity matrix, or a data frame/ matrix
...	further arguments passed to or from other methods.
clusters	clustering
fun	character name of the function to determine minimum distance between points in a cluster. Should be either mean, median or sum (default)
weights	ptional vector of weights for variables in data. See growdis in the FD package
data	data frame/ matrix

Details

mediod is the main function to compute the mediod, while mix.dist computes the distance between obersavations based on veriables of mix-types: binary, categorical, and continuous using the Gower's general similarity coefficient.

Value

data matrix of cluster mediods and the corresponding row indicies of the mediods in the original data

References

Gower, John C. "A general coefficient of similarity and some of its properties." Biometrics (1971): 857-871.

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