Error when using MLR3 for LIME

[DariusLR]

Hello,

I am using a MLR3 model, and want to apply the predictions of the model to LIME. I have read that a WrappedModel, as being produced by MLR3, should be compatible with LIME, as long as you generate separate data tables for when using the explain and lime function.

This is what I did:

`##Representative sample
set.seed(123)

#Create regression task
regression_task = TaskRegr$new(id = "Reviews", backend = Yelp_Complete_ML, target = "useful_votes")
print(regression_task)

#Create RF regression learner
Random_forest = mlr_learners$get("regr.ranger")

print(Random_forest)

#Set sample
data_train = sample(regression_task$nrow, 0.75 * regression_task$nrow)
data_test = setdiff(seq_len(regression_task$nrow), data_train)

#Train Random Forest
Model <- Random_forest$train(regression_task, row_ids = data_train)
print(Random_forest$model)

#Test Random Forest
prediction_RF <- Random_forest$predict(regression_task, row_ids = data_test)
print(prediction_RF)
head(as.data.table(prediction_RF))

#Measuring performance
measure_RF = msr("regr.mse")
prediction_RF$score(measure_RF)

#Data frame for LIME
sample <- sample.split(Yelp_Complete_ML, SplitRatio = .75)
data_train2 = subset(Yelp_Complete_ML, sample == TRUE)
data_test2 = subset(Yelp_Complete_ML, sample == FALSE)

#Using LIME for Random Forest
explainer_RF <- lime(data_train2, Model)
explanation <- explain(data_test2, explainer_RF, n_features = 1)`

After trying to run the explain function, I got the following error message:

Error: The class of model must have a model_type method. See ?model_type to get an overview of models supported out of the box

Then, I used the as_regressor function on the 'Model', in order to convert it. But after doing so, and running the following code:

`#Using LIME for Random Forest
explainer_RF <- lime(data_train2, as_regressor(Model))
explanation <- explain(data_test2, explainer_RF, n_features = 1)`

I got the following error:

Error in UseMethod("predict") :
no applicable method for 'predict' applied to an object of class "lime_regressor"

Could you take a look in this and help me out?

Kind regards,

Darius