C.f: Finding the center of a cluster.
In MKMeans: A Modern K-Means (MKMeans) Clustering Algorithm
C.f R Documentation
Finding the center of a cluster.
Description
It's a function of finding the center of a cluster.
Usage
C.f(dat, type)
Arguments
dat
Numeric. A cluster matrix with each row being an observaion.
type
Integer. The type of distance between observations. 1 for Euclidean distance. 2 for Manhattan distance. 3 for maximum deviation along dimensions.
Value
A vector.
Author(s)
Yarong Yang
References
Yarong Yang and Jacob Zhang.(2024) MKMeans: A Modern K-Means Clustering Algorithm.
Examples
x<-rnorm(5,0,1)
y<-rnorm(5,1,1)
data<-cbind(x,y)
Res<-C.f(dat=data,type=1)
MKMeans documentation built on Oct. 9, 2024, 1:07 a.m.
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| C.f | R Documentation |
Finding the center of a cluster.
Description
It's a function of finding the center of a cluster.
Usage
C.f(dat, type)
Arguments
dat |
Numeric. A cluster matrix with each row being an observaion. |
type |
Integer. The type of distance between observations. 1 for Euclidean distance. 2 for Manhattan distance. 3 for maximum deviation along dimensions. |
Value
A vector.
Author(s)
Yarong Yang
References
Yarong Yang and Jacob Zhang.(2024) MKMeans: A Modern K-Means Clustering Algorithm.
Examples
x<-rnorm(5,0,1)
y<-rnorm(5,1,1)
data<-cbind(x,y)
Res<-C.f(dat=data,type=1)
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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