Error in explain function with H2O GBM regression model - Error in if (r2 > max) { : missing value where TRUE/FALSE needed about lime HOT 4 CLOSED

library(tidyverse)
#> -- Attaching packages ------------------------------------ tidyverse 1.2.0 --
#> v ggplot2 2.2.1     v purrr   0.2.4
#> v tibble  1.3.4     v dplyr   0.7.4
#> v tidyr   0.7.2     v stringr 1.2.0
#> v readr   1.1.1     v forcats 0.2.0
#> -- Conflicts --------------------------------------- tidyverse_conflicts() --
#> x dplyr::filter() masks stats::filter()
#> x dplyr::lag()    masks stats::lag()
library(h2o)
#> 
#> ----------------------------------------------------------------------
#> 
#> Your next step is to start H2O:
#>     > h2o.init()
#> 
#> For H2O package documentation, ask for help:
#>     > ??h2o
#> 
#> After starting H2O, you can use the Web UI at http://localhost:54321
#> For more information visit http://docs.h2o.ai
#> 
#> ----------------------------------------------------------------------
#> 
#> Attaching package: 'h2o'
#> The following objects are masked from 'package:stats':
#> 
#>     cor, sd, var
#> The following objects are masked from 'package:base':
#> 
#>     %*%, %in%, &&, ||, apply, as.factor, as.numeric, colnames,
#>     colnames<-, ifelse, is.character, is.factor, is.numeric, log,
#>     log10, log1p, log2, round, signif, trunc
library(lime)
#> 
#> Attaching package: 'lime'
#> The following object is masked from 'package:dplyr':
#> 
#>     explain

dataset_url <- "https://www.dropbox.com/s/t3o1zvzq0t7emz4/sales.RDS?raw=1"
sales_aug <- readRDS(gzcon(url(dataset_url)))

train <- sales_aug %>% filter(month <= 8)
valid <- sales_aug %>% filter(month == 9)
test <- sales_aug %>% filter(month >= 10)

h2o.init()
#>  Connection successful!
#> 
#> R is connected to the H2O cluster: 
#>     H2O cluster uptime:         8 minutes 21 seconds 
#>     H2O cluster version:        3.14.0.7 
#>     H2O cluster version age:    19 days  
#>     H2O cluster name:           H2O_started_from_R_andre_crw711 
#>     H2O cluster total nodes:    1 
#>     H2O cluster total memory:   1.71 GB 
#>     H2O cluster total cores:    4 
#>     H2O cluster allowed cores:  4 
#>     H2O cluster healthy:        TRUE 
#>     H2O Connection ip:          localhost 
#>     H2O Connection port:        54321 
#>     H2O Connection proxy:       NA 
#>     H2O Internal Security:      FALSE 
#>     H2O API Extensions:         Algos, AutoML, Core V3, Core V4 
#>     R Version:                  R version 3.4.2 (2017-09-28)
h2o.no_progress()
train <- as.h2o(train)
valid <- as.h2o(valid)
test <- as.h2o(test)

y <- "amount"
x <- setdiff(names(train), y)

leaderboard <- h2o.automl(x, y, training_frame = train, validation_frame = valid, leaderboard_frame = test, max_runtime_secs = 30, stopping_metric = "MSE", seed = 12345)
gbm_model <- leaderboard@leader

explainer <- lime(as.data.frame(train), gbm_model, bin_continuous = FALSE)
explanation <- explain(as.data.frame(test[1:5,]), explainer, n_features = 5)
#> Warning in `[<-.factor`(`*tmp*`, iseq, value = structure(c(1L, 1L, 1L,
#> 1L, : invalid factor level, NA generated
#> Error in if (r2 > max) {: valor ausente donde TRUE/FALSE es necesario