i.e.
library(parsnip)
data("lending_club")
multi_reg <- multinom_reg(penalty = 0.01)
multi_reg_glmnet <- multi_reg %>% set_engine("glmnet")
multi_reg_fit <- fit(multi_reg_glmnet, verification_status ~ annual_inc + sub_grade, data = lending_club)
multi_reg_fit %>%
predict(new_data = lending_club, type = "prob")
#> # A tibble: 9,857 x 3
#> .pred_.pred_Not_Verified .pred_.pred_Source_Verified .pred_.pred_Verifi…
#> <dbl> <dbl> <dbl>
#> 1 0.312 0.389 0.298
#> 2 0.365 0.369 0.266
#> 3 0.341 0.383 0.277
#> 4 0.297 0.416 0.287
#> 5 0.387 0.377 0.236
#> 6 0.305 0.387 0.308
#> 7 0.366 0.366 0.268
#> 8 0.409 0.397 0.194
#> 9 0.365 0.380 0.255
#> 10 0.370 0.360 0.270
#> # … with 9,847 more rows
This is simply due to this line:
https://github.com/tidymodels/parsnip/blob/master/R/multinom_reg_data.R#L47
We don't need to add .pred_ to the names here, as it is done once in the formatting step at the end.
RetroSearch is an open source project built by @garambo | Open a GitHub Issue
Search and Browse the WWW like it's 1997 | Search results from DuckDuckGo
HTML:
3.2
| Encoding:
UTF-8
| Version:
0.7.4