Comments (3)
Thanks for this - I'll look into it. Next time do format example code as code so it is easier to run (I've done it for you this time).
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I can reproduce. Will debug
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Fixed in 02dcadd
The problem was that your test data was on the edge of the training data and you used binning of continuous variables. This resulted in a column of permutations that all were in the same bin. Zero-variance columns are now removed by default
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Related Issues (20)
- Exactly with same data GBM&Lime explain() works fine, but failing for RandomForest and CRF with NA/NaN/Inf in 'y'
- permute_cases: Error arguments imply differing number of rows: 30000, 0
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- Shiny plotOutput with plot_features from the lime package produces nothing
- Use of lime to be used in conjunction with keras model (regression)
- Error when using MLR3 for LIME
- lime/keras image classification: Input must be a vector, not a `superpixel_list` object. HOT 4
- [!] explain() does not work with ordered factors
- Flow ... through to the interactive_text_explanations
- Question about LIME results HOT 1
- Incorrect diagram in "Understanding lime"? HOT 1
- lime predicts other label than CNN
- Error in feature_distribution[[i]] : subscript out of bounds
- Error in cut.default(x[[i]], unique(explainer$bin_cuts[[i]]), labels = FALSE, : invalid number of intervals
- Error in Image Explanation
- Documentation gap concerning usage with additional libraries HOT 1
- Compatibility with tidymodels HOT 2
- Family in glmnet is always gaussian
- Release lime 0.5.3
- Error in combine_vars(data, params$plot_env, vars, drop = params$drop) :
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