Introduction to Modern Mathematical Modeling with R:

A User’s Manual to Train Mathematical Consultants

 

A Cambridge University Press book by

SSP Shen

 

 

R Code written by Dr. Samuel Shen, Distinguished Professor

San Diego State University, California, USA

https://shen.sdsu.edu

Email: sshen@sdsu.edu

 

Compiled and Edited by Joaquin Stawsky

San Diego State University, August 2022

 

 

 

Chapter 12: Concepts of Machine Learning

K-means Clustering

# K-Means Cluster Analysis for a 2D Random Point Set 
mydata <- matrix(runif(40),ncol=2)
fit <- kmeans(mydata, 5) # 5 cluster solution

# get cluster means 
aggregate(mydata,by=list(fit$cluster),FUN=mean)

##   Group.1        V1        V2
## 1       1 0.2720483 0.1078595
## 2       2 0.1232850 0.7844528
## 3       3 0.4362333 0.5604447
## 4       4 0.7399861 0.8053710
## 5       5 0.7914742 0.4243538

# append cluster assignment
mycluster <- data.frame(mydata, fit$cluster) 
library(animation)

## Warning: package 'animation' was built under R version 4.1.3

kmeans.ani(mycluster, centers=5, pch=1:5, col=1:5)