# PREPARING FOR THE ANALYSIS

## Install and load the package ppclust

This vignette is designed to be used with the ppclust package. You can download the recent version of the package ‘`ppclust`

’ from CRAN with the following command:

`install.packages("ppclust")`

If you have already installed ‘`ppclust`

’, you can load it into R working environment by using the following command:

## Load the required packages

For visualization of the clustering results, some examples in this vignette use the functions from some cluster analysis packages such as ‘`cluster`

’, ‘`fclust`

’ and ‘`factoextra`

’. Therefore, these packages should be loaded into R working environment with the following commands:

```
library(factoextra)
library(cluster)
library(fclust)
```

## Load the data set

We demonstrate FCM on the Iris data set (Anderson, 1935). It is a real data set of the four features (Sepal.Length, Sepal.Width, Petal.Length and Petal.Width) of 150 iris flowers with three species (in the last column as the class variable). This four-dimensional data set contains 50 samples each of three iris species. One of these three natural clusters (Class 1) is linearly well-separated from the other two clusters, while Classes 2 and 3 have some overlap as seen in the plot below.

Plot the data by the classes of iris species