--- title: | | STAT 408 - Statistical Learning | Clustering date: "April 3, 2018" output: html_document --- ```{r setup, include=FALSE} library(ggplot2) library(dplyr) library(knitr) library(randomForest) library(maps) library(plotrix) library(mnormt) library(rpart) knitr::opts_chunk\$set(echo = TRUE) knitr::knit_hooks\$set(mysize = function(before, options, envir) { if (before) return(options\$size) }) ``` ## Lecture Exercise: Clustering Zoo Animals Use the dataset create below for the following questions. ```{r, echo=T, mysize=TRUE, size='\\tiny',eval=F} zoo.data <- read.csv('http://www.math.montana.edu/ahoegh/teaching/stat408/datasets/ZooClean.csv') rownames(zoo.data) <- zoo.data[,1] zoo.data <- zoo.data[,-1] ``` - Use multidimensional scaling to visualize the data in two dimensions. - What are two animals that are very similar and two that are very different? - Create a hierachical clustering object for this dataset. Why are a leopard and raccoon clustered together for any cluster size? - Now add colors corresponding to four different clusters to your MDS plot. Interpret what each of the four clusters correspond to.