The problem
I'm encountering an inconsistency with generating probability predictions for two class GAM models. The predictions are being returned as arrays within a tibble, rather than just a tibble of numeric values. I believe this issue arises because mgcv returns an array of predictions, rather than a vector.
Issue #541 covers a similar issue around GAM class predictions where mgcv's prediction format was also the source of the problem. I believe the fix for this problem would closely mirror the fix for that issue (fix #542).
Reproducible example
library(parsnip)
set.seed(33)
twoClassSim <- caret::twoClassSim()
gam <- gen_additive_mod() |>
set_mode("classification") |>
fit(Class ~ Linear01,
data = twoClassSim)
pred <- predict(gam, head(twoClassSim), type = "prob")
# demonstrating error
class(pred$.pred_Class1)
#> [1] "array"
dplyr::glimpse(pred)
#> Rows: 6
#> Columns: 2
#> $ .pred_Class1 <dbl> <array[6]>
#> $ .pred_Class2 <dbl> <array[6]>
# session information
sessionInfo()
#> R version 4.2.0 (2022-04-22)
#> Platform: aarch64-apple-darwin20 (64-bit)
#> Running under: macOS Monterey 12.3.1
#>
#> Matrix products: default
#> BLAS: /Library/Frameworks/R.framework/Versions/4.2-arm64/Resources/lib/libRblas.0.dylib
#> LAPACK: /Library/Frameworks/R.framework/Versions/4.2-arm64/Resources/lib/libRlapack.dylib
#>
#> locale:
#> [1] en_US.UTF-8/en_US.UTF-8/en_US.UTF-8/C/en_US.UTF-8/en_US.UTF-8
#>
#> attached base packages:
#> [1] stats graphics grDevices utils datasets methods base
#>
#> other attached packages:
#> [1] parsnip_0.2.1
#>
#> loaded via a namespace (and not attached):
#> [1] Rcpp_1.0.8.3 lubridate_1.8.0 lattice_0.20-45
#> [4] listenv_0.8.0 tidyr_1.2.0 class_7.3-20
#> [7] digest_0.6.29 ipred_0.9-12 foreach_1.5.2
#> [10] utf8_1.2.2 parallelly_1.31.1 R6_2.5.1
#> [13] plyr_1.8.7 stats4_4.2.0 reprex_2.0.1
#> [16] hardhat_0.2.0 evaluate_0.15 ggplot2_3.3.5
#> [19] highr_0.9 pillar_1.7.0 rlang_1.0.2
#> [22] caret_6.0-92 data.table_1.14.2 rstudioapi_0.13
#> [25] rpart_4.1.16 Matrix_1.4-1 rmarkdown_2.14
#> [28] splines_4.2.0 gower_1.0.0 stringr_1.4.0
#> [31] munsell_0.5.0 compiler_4.2.0 xfun_0.30
#> [34] pkgconfig_2.0.3 mgcv_1.8-40 globals_0.14.0
#> [37] htmltools_0.5.2 nnet_7.3-17 tidyselect_1.1.2
#> [40] tibble_3.1.6 prodlim_2019.11.13 codetools_0.2-18
#> [43] fansi_1.0.3 future_1.25.0 crayon_1.5.1
#> [46] dplyr_1.0.9 withr_2.5.0 ModelMetrics_1.2.2.2
#> [49] MASS_7.3-56 recipes_0.2.0 grid_4.2.0
#> [52] nlme_3.1-157 gtable_0.3.0 lifecycle_1.0.1
#> [55] magrittr_2.0.3 pROC_1.18.0 scales_1.2.0
#> [58] future.apply_1.9.0 cli_3.3.0 stringi_1.7.6
#> [61] reshape2_1.4.4 fs_1.5.2 timeDate_3043.102
#> [64] ellipsis_0.3.2 generics_0.1.2 vctrs_0.4.1
#> [67] lava_1.6.10 iterators_1.0.14 tools_4.2.0
#> [70] glue_1.6.2 purrr_0.3.4 parallel_4.2.0
#> [73] fastmap_1.1.0 survival_3.3-1 yaml_2.3.5
#> [76] colorspace_2.0-3 knitr_1.39Created on 2022-04-28 by the reprex package (v2.0.1)
The problem
I'm encountering an inconsistency with generating probability predictions for two class GAM models. The predictions are being returned as arrays within a tibble, rather than just a tibble of numeric values. I believe this issue arises because
mgcvreturns an array of predictions, rather than a vector.Issue #541 covers a similar issue around GAM class predictions where
mgcv's prediction format was also the source of the problem. I believe the fix for this problem would closely mirror the fix for that issue (fix #542).Reproducible example
Created on 2022-04-28 by the reprex package (v2.0.1)