revdep/checks.noindex/waywiser/old/waywiser.Rcheck/tests/testthat/_snaps/srr-ww_area_of_applicability.md

In AFIT-R/vip: Variable Importance Plots

srr: expected failures for ww_area_of_applicability

Code
  ww_area_of_applicability(y ~ ., train, test, importance)
Condition
  Error in `ww_area_of_applicability()`:
  ! All variables in `data` and `testing` must inherit either numeric or integer classes.

Code
  ww_area_of_applicability(train, test, importance)
Condition
  Error:
  ! All predictors must be numeric.

Code
  ww_area_of_applicability(comb_rset_no_y, importance = importance)
Condition
  Error in `purrr::map()`:
  i In index: 1.
  Caused by error in `purrr::map()`:
  ! All predictors must be numeric.

Code
  ww_area_of_applicability(y ~ ., train, test, importance)
Condition
  Error in `model.frame.default()`:
  ! invalid type (list) for variable 'x3'

Code
  ww_area_of_applicability(train, test, importance)
Condition
  Error:
  ! All predictors must be numeric.

Code
  ww_area_of_applicability(comb_rset_no_y, importance = importance)
Condition
  Error in `purrr::map()`:
  i In index: 1.
  Caused by error in `purrr::map()`:
  ! All predictors must be numeric.

Code
  ww_area_of_applicability(y ~ ., head(train, 0), test, importance)
Condition
  Error in `create_aoa()`:
  ! 0 rows were passed as training data.

Code
  ww_area_of_applicability(y ~ ., train, head(test, 0), importance)
Condition
  Error in `create_aoa()`:
  ! 0 rows were passed as testing data.

Code
  ww_area_of_applicability(head(train[2:11], 0), test[2:11], importance)
Condition
  Error in `create_aoa()`:
  ! 0 rows were passed as training data.

Code
  ww_area_of_applicability(train[2:11], head(test[2:11], 0), importance)
Condition
  Error in `create_aoa()`:
  ! 0 rows were passed as testing data.

Code
  ww_area_of_applicability(head(as.matrix(train[2:11]), 0), as.matrix(test[2:11]),
  importance)
Condition
  Error in `create_aoa()`:
  ! 0 rows were passed as training data.

Code
  ww_area_of_applicability(as.matrix(train[2:11]), head(as.matrix(test[2:11]), 0),
  importance)
Condition
  Error in `create_aoa()`:
  ! 0 rows were passed as testing data.

Code
  ww_area_of_applicability(y ~ ., train_na, test, importance)
Condition
  Error in `create_aoa()`:
  ! Missing values in training data.
  i Either process your data to fix NA values, or set `na_rm = TRUE`.

Code
  ww_area_of_applicability(y ~ ., train, test_na, importance)
Condition
  Error in `check_di_testing()`:
  ! Missing values in testing data.
  i Either process your data to fix NA values, or set `na_rm = TRUE`.

Code
  ww_area_of_applicability(train_na[2:11], test[2:11], importance)
Condition
  Error in `create_aoa()`:
  ! Missing values in training data.
  i Either process your data to fix NA values, or set `na_rm = TRUE`.

Code
  ww_area_of_applicability(train[2:11], test_na[2:11], importance)
Condition
  Error in `check_di_testing()`:
  ! Missing values in testing data.
  i Either process your data to fix NA values, or set `na_rm = TRUE`.

Code
  ww_area_of_applicability(as.matrix(train_na[2:11]), as.matrix(test[2:11]),
  importance)
Condition
  Error in `create_aoa()`:
  ! Missing values in training data.
  i Either process your data to fix NA values, or set `na_rm = TRUE`.

Code
  ww_area_of_applicability(as.matrix(train[2:11]), as.matrix(test_na[2:11]),
  importance)
Condition
  Error in `check_di_testing()`:
  ! Missing values in testing data.
  i Either process your data to fix NA values, or set `na_rm = TRUE`.

Code
  ww_area_of_applicability(comb_rset_no_y_train_na, importance = importance)
Condition
  Error in `purrr::map()`:
  i In index: 1.
  Caused by error in `create_aoa()`:
  ! Missing values in training data.
  i Either process your data to fix NA values, or set `na_rm = TRUE`.

Code
  ww_area_of_applicability(comb_rset_no_y, comb_rset_no_y_test_na, importance)
Condition
  Error in `purrr::map()`:
  i In index: 1.
  Caused by error in `purrr::map()`:
  ! All predictors must be numeric.

Code
  ww_area_of_applicability(y ~ ., train, train, importance)
Condition
  Warning:
  The AOA threshold was 0, which is usually unexpected.
  i Did you accidentally pass the same data as testing and training?
Output
  # Predictors:
     10
  Area-of-applicability threshold:
     0

Code
  ww_area_of_applicability(train[2:11], train[2:11], importance)
Condition
  Warning:
  The AOA threshold was 0, which is usually unexpected.
  i Did you accidentally pass the same data as testing and training?
Output
  # Predictors:
     10
  Area-of-applicability threshold:
     0

Code
  ww_area_of_applicability(as.matrix(train[2:11]), as.matrix(train[2:11]),
  importance)
Condition
  Warning:
  The AOA threshold was 0, which is usually unexpected.
  i Did you accidentally pass the same data as testing and training?
Output
  # Predictors:
     10
  Area-of-applicability threshold:
     0

Code
  ww_area_of_applicability(comb_rset_no_y_identical, importance = importance)
Condition
  Warning:
  The AOA threshold was 0, which is usually unexpected.
  i Did you accidentally pass the same data as testing and training?
Output
  # Predictors:
     10
  Area-of-applicability threshold:
     0

AFIT-R/vip documentation built on Aug. 22, 2023, 8:59 a.m.