**Modelwordcloud** is a package that makes a word cloud out of text, primarially based on the associations between that text and a predictive model.

```{R, eval=TRUE} data(iris) model <- lm(Petal.Width ~ Species, iris) summary(model)

As we can see, setosa (represented by the intercept) is the least associated with Petal.Width, wheras virginica is the most associated. We can show this in a word cloud: ```{R, eval=TRUE} words_and_freqs <- rle(as.character(iris$Species)) freqs <- words_and_freqs$lengths words <- words_and_freqs$values coefficients <- model$coefficients colors <- c("red", "orange", "blue") # Least associated gets red, most associated gets blue. library(modelwordcloud) wordcloud(words = words, freq = freqs, coefficients = coefficients, colors = colors)

You can also pass in the model object directly, if desired.

```{R, eval=TRUE} wordcloud(model, colors = colors)

## Installation This package can be installed from CRAN: ```R install.packages("modelwordcloud")

This work is based upon the wordcloud package by Ian Fellows, available from CRAN with the LGPL-2.1 license. This derivative work modified the original wordcloud package library by adding in logic to color words based on an additional variable, `coefficients`

. The code was also cleaned, re-styled, and simplified. This package also removed some unneeded functionality from the wordcloud package, such as a C library for calculating overlap.

- the colormap package helps produce large color palletes for use with
`wordcloud`

.

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