Regression Example #33
Description
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 dimensionsI 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.