deepMOU (version 0.1.1)

words_freq_plot: 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.

Value

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

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

Examples

# NOT RUN {
# 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" )

# }