Hi everyone! This is a question that combines questions about {caret}, {nnet}, multinomial logistic regression, and how to interpret the results of the functions of those packages.

I am trying to calculate and interpret the variable importance of a *multinomial logistic regression* I built using the `multinom()`

function from the {nnet} R package. I want to measure the variable importance of each predictor variable contributing to the outcome variable, and the documentation of {caret} says that its function `varImp()`

can do that. On the surface the code works in terms of generating some importance values, but what it doesn't do (I think - in the documentation or the function itself) is tell me how these values are calculated or what they actually are.

Here's my attempt at a reprex:

```
library(tidyverse)
library(nnet)
library(caret)
fit <- multinom(Species ~ ., data = iris) # fit model
varImp(fit)
```

And this is what I get:

```
Overall
Sepal.Length 13.38206
Sepal.Width 24.07817
Petal.Length 37.90455
Petal.Width 18.23298
```

My question is - **what do these numbers mean**, or how can I find out what they mean? (I've tried the package documentation) Is there an alternative way where I can get an estimate of the relative variable importance?

Thank you!

(Sorry - I've posted this question once on Stack Overflow but didn't get answer...)