words_freq_plot {deepMOU} R Documentation

## Graph of most frequent words of each cluster

### Description

Graphical plot of the most frequent words of each cluster

### Usage

words_freq_plot(
x,
clusters,
clust_label = NULL,
n_words = 5,
words_size = 2,
axis_size = 1,
set_colors = NA,
main = "Most frequent words for each cluster",
xlabel = "",
ylabel = ""
)


### Arguments

 x Document-term matrix describing the frequency of terms that occur in a collection of documents. Rows correspond to documents in the collection and columns correspond to terms. clusters Integer vector of length of the number of cases, which indicates a clustering. The clusters have to be numbered from 1 to the number of clusters. clust_label Vector of length of the number of cluster containing the cluster names to be displayed (by default "Cluster_1", "Cluster_2", ...). n_words Number of words to display. words_size A numerical value giving the amount by which plotting words should be magnified with respect to the default setting. axis_size Magnification to be used for axis annotation with respect to the default setting. set_colors Choose palette for word colors. main A title for the plot. Default is "Most frequent words for each cluster". xlabel A title for the x-axis. Default is empty. ylabel A title for the y-axis. Default is empty.

### Details

The number of most frequent words to be shown can be set by n_words and also clusters names can be passed beforehand as a character vector to clust_label

### Value

A graphical aid for visualizing the most frequent terms for each cluster.

### Examples

# Load the CNAE2 dataset
data("CNAE2")

# Perform parameter estimation and clustering
mou_CNAE2 = mou_EM(x = CNAE2, k = 2)

# Usage of the function
words_freq_plot(mou_CNAE2$x, mou_CNAE2$clusters,n_words = 4, words_size = 2, main = "Example" )



[Package deepMOU version 0.1.1 Index]