Skip to content

Error during explain with H2O GBM/XGB models - "NA/NaN/Inf in 'x'" #45

Closed
@dkincaid

Description

@dkincaid

I'm trying to use the package with an H2O xgboost model (I've also tried it with GBM and get the same thing. The error is:

Error in glm.fit(x = x_fit, y = y, weights = weights, family = gaussian()) : 
  NA/NaN/Inf in 'x'

Here is the code I'm running:

explainer <- lime::lime(as.data.frame(wellnessTrain), mdl)

explanation <- lime::explain(as.data.frame(wellnessTest),
                       explainer, n_labels = 1, n_features = 2)

This is caused by having some NA values in the data frame, but I thought that this had already been fixed in issue #8. I verified this by removing the three columns that have NA values as a test. These NA values are meaningful and H2O's GBM and XGBoost handle them by creating a category for the missing value after binning the unmissing feature values. Is there any easy fix here?

Metadata

Metadata

Assignees

No one assigned

    Labels

    No labels
    No labels

    Projects

    No projects

    Milestone

    No milestone

    Relationships

    None yet

    Development

    No branches or pull requests

    Issue actions