remove tailor(type)

doesn't yet check for compatibility between adjustments pre-fit

Author: simonpcouch

R/tailor.R

@@ -19,9 +19,6 @@
 #' with the [tidymodels](https://tidymodels.org) framework; for greatest ease
 #' of use, situate tailors in model workflows with `?workflows::add_tailor()`.
 #'
-#' @param type Character. The model sub-mode. Possible values are
-#' `"unknown"`, `"regression"`, `"binary"`, or `"multiclass"`. Only required
-#' when used independently of `?workflows::add_tailor()`.
 #' @param outcome <[`tidy-select`][dplyr::dplyr_tidy_select]> Only required
 #' when used independently of `?workflows::add_tailor()`, and can also be passed
 #' at `fit()` time instead. The column name of the outcome variable.
@@ -64,18 +61,16 @@
 #' # adjust hard class predictions
 #' predict(tlr_fit, two_class_example) %>% count(predicted)
 #' @export
-tailor <- function(type = "unknown", outcome = NULL, estimate = NULL,
-                      probabilities = NULL) {
+tailor <- function(outcome = NULL, estimate = NULL, probabilities = NULL) {
   columns <-
     list(
       outcome = outcome,
-      type = type,
       estimate = estimate,
       probabilities = probabilities
     )
 
   new_tailor(
-    type,
+    "unknown",
     adjustments = list(),
     columns = columns,
     ptype = tibble::new_tibble(list()),

man/tailor.Rd

@@ -20,15 +20,7 @@
 ---
 
     Code
-      tailor("binary") %>% adjust_numeric_calibration("linear")
-    Condition
-      Error in `adjust_numeric_calibration()`:
-      ! A binary tailor is incompatible with the adjustment `adjust_numeric_calibration()`.
-
----
-
-    Code
-      tailor("regression") %>% adjust_numeric_calibration("binary")
+      tailor() %>% adjust_numeric_calibration("binary")
     Condition
       Error in `adjust_numeric_calibration()`:
       ! `method` must be one of "linear", "isotonic", or "isotonic_boot", not "binary".

tests/testthat/_snaps/adjust-numeric-calibration.md

@@ -20,15 +20,7 @@
 ---
 
     Code
-      tailor("regression") %>% adjust_probability_calibration("binary")
-    Condition
-      Error in `adjust_probability_calibration()`:
-      ! A regression tailor is incompatible with the adjustment `adjust_probability_calibration()`.
-
----
-
-    Code
-      tailor("binary") %>% adjust_probability_calibration("linear")
+      tailor() %>% adjust_probability_calibration("linear")
     Condition
       Error in `adjust_probability_calibration()`:
       ! `method` must be one of "logistic", "multinomial", "beta", "isotonic", or "isotonic_boot", not "linear".

tests/testthat/_snaps/adjust-probability-calibration.md

@@ -10,32 +10,31 @@
 ---
 
     Code
-      tailor(type = "binary")
+      tailor()
     Message
       
       -- tailor ----------------------------------------------------------------------
-      A binary postprocessor with 0 adjustments.
+      A postprocessor with 0 adjustments.
 
 ---
 
     Code
-      tailor(type = "binary") %>% adjust_probability_threshold(0.2)
+      tailor() %>% adjust_probability_threshold(0.2)
     Message
       
       -- tailor ----------------------------------------------------------------------
-      A binary postprocessor with 1 adjustment:
+      A postprocessor with 1 adjustment:
       
       * Adjust probability threshold to 0.2.
 
 ---
 
     Code
-      tailor(type = "binary") %>% adjust_probability_threshold(0.2) %>%
-        adjust_equivocal_zone()
+      tailor() %>% adjust_probability_threshold(0.2) %>% adjust_equivocal_zone()
     Message
       
       -- tailor ----------------------------------------------------------------------
-      A binary postprocessor with 2 adjustments:
+      A postprocessor with 2 adjustments:
       
       * Adjust probability threshold to 0.2.
       * Add equivocal zone of size 0.1.

tests/testthat/_snaps/tailor.md

@@ -1,7 +1,7 @@
 # validation of adjustments (regression)
 
     Code
-      tailor(type = "regression") %>% adjust_numeric_range(lower_limit = 2) %>%
+      tailor() %>% adjust_numeric_range(lower_limit = 2) %>%
         adjust_numeric_calibration() %>% adjust_predictions_custom(squared = .pred^2)
     Condition
       Error in `adjust_numeric_calibration()`:
@@ -10,7 +10,7 @@
 # validation of adjustments (classification)
 
     Code
-      tailor(type = "binary") %>% adjust_probability_threshold(threshold = 0.4) %>%
+      tailor() %>% adjust_probability_threshold(threshold = 0.4) %>%
         adjust_probability_calibration()
     Condition
       Error in `adjust_probability_calibration()`:
@@ -28,7 +28,7 @@
 ---
 
     Code
-      tailor(type = "binary") %>% adjust_predictions_custom(veg = "potato") %>%
+      tailor() %>% adjust_predictions_custom(veg = "potato") %>%
         adjust_probability_threshold(threshold = 0.4) %>%
         adjust_probability_calibration()
     Condition
@@ -48,7 +48,7 @@
 ---
 
     Code
-      tailor(type = "binary") %>% adjust_predictions_custom(veg = "potato") %>%
+      tailor() %>% adjust_predictions_custom(veg = "potato") %>%
         adjust_probability_threshold(threshold = 0.4) %>%
         adjust_probability_threshold(threshold = 0.5) %>%
         adjust_probability_calibration()
@@ -70,7 +70,7 @@
 ---
 
     Code
-      tailor(type = "binary") %>% adjust_equivocal_zone(value = 0.2) %>%
+      tailor() %>% adjust_equivocal_zone(value = 0.2) %>%
         adjust_probability_threshold(threshold = 0.4)
     Condition
       Error in `adjust_probability_threshold()`:

tests/testthat/_snaps/validation-rules.md

@@ -44,11 +44,7 @@ test_that("errors informatively with bad input", {
   expect_snapshot(error = TRUE, adjust_numeric_calibration(tailor(), "boop"))
   expect_snapshot(
     error = TRUE,
-    tailor("binary") %>% adjust_numeric_calibration("linear")
-  )
-  expect_snapshot(
-    error = TRUE,
-    tailor("regression") %>% adjust_numeric_calibration("binary")
+    tailor() %>% adjust_numeric_calibration("binary")
   )
 
   expect_no_condition(adjust_numeric_calibration(tailor()))

tests/testthat/test-adjust-numeric-calibration.R

@@ -54,11 +54,7 @@ test_that("errors informatively with bad input", {
   expect_snapshot(error = TRUE, adjust_probability_calibration(tailor(), "boop"))
   expect_snapshot(
     error = TRUE,
-    tailor("regression") %>% adjust_probability_calibration("binary")
-  )
-  expect_snapshot(
-    error = TRUE,
-    tailor("binary") %>% adjust_probability_calibration("linear")
+    tailor() %>% adjust_probability_calibration("linear")
   )
 
   expect_no_condition(adjust_numeric_calibration(tailor()))

tests/testthat/test-adjust-probability-calibration.R

@@ -1,12 +1,12 @@
 test_that("tailor printing", {
   expect_snapshot(tailor())
-  expect_snapshot(tailor(type = "binary"))
+  expect_snapshot(tailor())
   expect_snapshot(
-    tailor(type = "binary") %>%
+    tailor() %>%
       adjust_probability_threshold(.2)
   )
   expect_snapshot(
-    tailor(type = "binary") %>%
+    tailor() %>%
       adjust_probability_threshold(.2) %>%
       adjust_equivocal_zone()
   )

tests/testthat/test-tailor.R

@@ -1,15 +1,15 @@
 test_that("validation of adjustments (regression)", {
   expect_no_condition(
     reg_tailor <-
-      tailor(type = "regression") %>%
+      tailor() %>%
       adjust_numeric_calibration() %>%
       adjust_numeric_range(lower_limit = 2) %>%
       adjust_predictions_custom(squared = .pred^2)
   )
 
   expect_snapshot(
     error = TRUE,
-    tailor(type = "regression") %>%
+    tailor() %>%
       adjust_numeric_range(lower_limit = 2) %>%
       adjust_numeric_calibration() %>%
       adjust_predictions_custom(squared = .pred^2)
@@ -19,7 +19,7 @@ test_that("validation of adjustments (regression)", {
   # modifies the prediction?
   expect_no_condition(
     reg_tailor <-
-      tailor(type = "regression") %>%
+      tailor() %>%
       adjust_predictions_custom(squared = .pred^2) %>%
       adjust_numeric_calibration() %>%
       adjust_numeric_range(lower_limit = 2)
@@ -29,14 +29,14 @@ test_that("validation of adjustments (regression)", {
 test_that("validation of adjustments (classification)", {
   expect_no_condition(
     cls_tailor_1 <-
-      tailor(type = "binary") %>%
+      tailor() %>%
       adjust_probability_calibration("logistic") %>%
       adjust_probability_threshold(threshold = .4)
   )
 
   expect_no_condition(
     cls_tailor_2 <-
-      tailor(type = "binary") %>%
+      tailor() %>%
       adjust_predictions_custom(starch = "potato") %>%
       adjust_predictions_custom(veg = "green beans") %>%
       adjust_probability_calibration("logistic") %>%
@@ -45,7 +45,7 @@ test_that("validation of adjustments (classification)", {
 
   expect_snapshot(
     error = TRUE,
-    tailor(type = "binary") %>%
+    tailor() %>%
       adjust_probability_threshold(threshold = .4) %>%
       adjust_probability_calibration()
   )
@@ -59,7 +59,7 @@ test_that("validation of adjustments (classification)", {
 
   expect_snapshot(
     error = TRUE,
-    tailor(type = "binary") %>%
+    tailor() %>%
       adjust_predictions_custom(veg = "potato") %>%
       adjust_probability_threshold(threshold = .4) %>%
       adjust_probability_calibration()
@@ -75,7 +75,7 @@ test_that("validation of adjustments (classification)", {
 
   expect_snapshot(
     error = TRUE,
-    tailor(type = "binary") %>%
+    tailor() %>%
       adjust_predictions_custom(veg = "potato") %>%
       adjust_probability_threshold(threshold = .4) %>%
       adjust_probability_threshold(threshold = .5) %>%
@@ -93,7 +93,7 @@ test_that("validation of adjustments (classification)", {
 
   expect_snapshot(
     error = TRUE,
-    tailor(type = "binary") %>%
+    tailor() %>%
       adjust_equivocal_zone(value = .2) %>%
       adjust_probability_threshold(threshold = .4)
   )