add a line ending to printed notes

[topepo]

For some notes, show_notes() would not properly break the lines:

library(tidymodels)
set.seed(1)
dat <- sim_classification(150, intercept = 15)
rs <- vfold_cv(dat)
fit_lr <- 
  logistic_reg() %>% 
  fit_resamples(
  class ~ .,
  rs,
  metrics = metric_set(accuracy, kap, recall, precision)
)
#> ! Fold01: preprocessor 1/1, model 1/1: glm.fit: algorithm did not converge
#> ! Fold02: preprocessor 1/1, model 1/1: glm.fit: algorithm did not converge, glm.fit: fitted probabilities numer...
#> ! Fold03: preprocessor 1/1, model 1/1: glm.fit: algorithm did not converge, glm.fit: fitted probabilities numer...
#> ! Fold04: preprocessor 1/1, model 1/1: glm.fit: algorithm did not converge, glm.fit: fitted probabilities numer...
#> ! Fold05: preprocessor 1/1, model 1/1: glm.fit: algorithm did not converge, glm.fit: fitted probabilities numer...
#> ! Fold06: preprocessor 1/1, model 1/1: glm.fit: algorithm did not converge, glm.fit: fitted probabilities numer...
#> ! Fold07: preprocessor 1/1, model 1/1: glm.fit: algorithm did not converge, glm.fit: fitted probabilities numer...
#> ! Fold08: preprocessor 1/1, model 1/1: glm.fit: algorithm did not converge, glm.fit: fitted probabilities numer...
#> ! Fold09: preprocessor 1/1, model 1/1: glm.fit: algorithm did not converge, glm.fit: fitted probabilities numer...
#> ! Fold10: preprocessor 1/1, model 1/1: glm.fit: algorithm did not converge, glm.fit: fitted probabilities numer...
show_notes(fit_lr)
#> unique notes:
#> ───────────────────────────────────
#> glm.fit: algorithm did not converge ───────────────────────────────────
#> glm.fit: algorithm did not converge, glm.fit: fitted probabilities numerically 0 or 1 occurred

^{Created on 2022-09-30 by the reprex package (v2.0.1)}

For this new version:

library(tidymodels)
set.seed(1)
dat <- sim_classification(150, intercept = 15)
rs <- vfold_cv(dat)
fit_lr <- 
  logistic_reg() %>% 
  fit_resamples(
  class ~ .,
  rs,
  metrics = metric_set(accuracy, kap, recall, precision)
)
#> ! Fold01: preprocessor 1/1, model 1/1: glm.fit: algorithm did not converge
#> ! Fold02: preprocessor 1/1, model 1/1: glm.fit: algorithm did not converge, glm.fit: fitted probabilities numer...
#> ! Fold03: preprocessor 1/1, model 1/1: glm.fit: algorithm did not converge, glm.fit: fitted probabilities numer...
#> ! Fold04: preprocessor 1/1, model 1/1: glm.fit: algorithm did not converge, glm.fit: fitted probabilities numer...
#> ! Fold05: preprocessor 1/1, model 1/1: glm.fit: algorithm did not converge, glm.fit: fitted probabilities numer...
#> ! Fold06: preprocessor 1/1, model 1/1: glm.fit: algorithm did not converge, glm.fit: fitted probabilities numer...
#> ! Fold07: preprocessor 1/1, model 1/1: glm.fit: algorithm did not converge, glm.fit: fitted probabilities numer...
#> ! Fold08: preprocessor 1/1, model 1/1: glm.fit: algorithm did not converge, glm.fit: fitted probabilities numer...
#> ! Fold09: preprocessor 1/1, model 1/1: glm.fit: algorithm did not converge, glm.fit: fitted probabilities numer...
#> ! Fold10: preprocessor 1/1, model 1/1: glm.fit: algorithm did not converge, glm.fit: fitted probabilities numer...
show_notes(fit_lr)
#> unique notes:
#> ───────────────────────────────────
#> glm.fit: algorithm did not converge 
#>  ───────────────────────────────────
#> glm.fit: algorithm did not converge, glm.fit: fitted probabilities numerically 0 or 1 occurred

^{Created on 2022-09-30 by the reprex package (v2.0.1)}

[github-actions]

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