Regression Example

[joshualeond]

Hi Thomas, thanks for your work here! I wanted to test the regression functionality similar to the python lime example here.

Everything seems to work correctly until the call to explain. Here is my reprex:

library(caret)
#> Loading required package: lattice
#> Loading required package: ggplot2
library(lime)

# load data
boston <- MASS::Boston

# Split up the data set
boston_test <- boston[1:100, 1:13]
boston_train <- boston[-(1:100), 1:13]
boston_lab <- boston[[14]][-(1:100)]

# Create Random Forest model on boston data
model_reg <- train(boston_train, boston_lab, method = 'rf')
#> randomForest 4.6-12
#> Type rfNews() to see new features/changes/bug fixes.
#> 
#> Attaching package: 'randomForest'
#> The following object is masked from 'package:ggplot2':
#> 
#>     margin

# Create an explainer object
explainer_reg <- lime(boston_train, model_reg)

# Explain new observation
explanation_reg <- explain(
  boston_test, 
  explainer_reg, 
  labels = NULL, 
  n_labels = 1, 
  n_features = 5
  )
#> Warning in explain.data.frame(boston_test, explainer_reg, labels = NULL, :
#> "labels" and "n_labels" arguments are ignored when explaining regression
#> models
#> Error in y[1, ]: incorrect number of dimensions

I may be missing something obvious but I haven't discovered it yet. Also as a note, if I attempt to leave the labels and n_labels arguments out of the function call it throws an error. Thanks again.

[thomasp85]

You seem to have stumbled upon a bug - I'll look into it. Thanks

[Marouds]

Hi @joshualeond & @thomasp85,

I am having the exact same problem as Joshua with my random forest.
I don't know what to put as "labels" and "n_labels" in order to solve it?
Did you manage?

Thank you very much in advance.
Maroussia

[joshualeond]

Hey @Marouds, I was able to run this example without any errors. This original bug resulted in the error:
#> Error in y[1, ]: incorrect number of dimensions

You're receiving this same error? Are you receiving this error using the example above or are you working with different data?

For a regression model you can remove the labels and n_labels arguments from the function call. Either way though, the explain() function should run without errors on this example.

[Marouds]

Hi @joshualeond, thank you very much for your quick reply!

I managed to run it in the end !! And indeed I was receiving the same error "#> Error in y[1, ]: incorrect number of dimensions". I added "drop=FALSE" when I split my data into training and testing dataset, and it worked!
(I might be using an old version of R)

Thanks!
Have a nice day

[Marouds]

I do have an issue with the visualization of the results, using plot_features().
It does not appear with colors and everything like it seems it should...
I don't know whether an addition packages was needed?
Thanks!!