Nothing
The `options` argument of `step_nzv()` was deprecated in recipes 0.1.7 and is now defunct.
i Please use the arguments `freq_cut` and `unique_cut` instead.
Code
recipe(~., data = mtcars) %>% step_nzv(options = list(freq_cut = 95 / 5,
unique_cut = 20))
Condition
Error:
! The `options` argument of `step_nzv()` was deprecated in recipes 0.1.7 and is now defunct.
i Please use the arguments `freq_cut` and `unique_cut` instead.
Code
recipe(~., dat_caseweights_x2) %>% step_nzv(all_predictors(), freq_cut = exp_freq_cut_int) %>%
prep()
Message
-- Recipe ----------------------------------------------------------------------
-- Inputs
Number of variables by role
predictor: 4
case_weights: 1
-- Training information
Training data contained 50 data points and no incomplete rows.
-- Operations
* Sparse, unbalanced variable filter removed: x4 | Trained, weighted
Code
recipe(~., dat_caseweights_y) %>% step_nzv(all_predictors(), freq_cut = exp_freq_cut_frag -
1e-04) %>% prep()
Message
-- Recipe ----------------------------------------------------------------------
-- Inputs
Number of variables by role
predictor: 4
case_weights: 1
-- Training information
Training data contained 50 data points and no incomplete rows.
-- Operations
* Sparse, unbalanced variable filter removed: x3 and x4 | Trained, ignored
weights
Code
rec
Message
-- Recipe ----------------------------------------------------------------------
-- Inputs
Number of variables by role
outcome: 1
predictor: 10
-- Operations
* Sparse, unbalanced variable filter on: <none>
Code
rec
Message
-- Recipe ----------------------------------------------------------------------
-- Inputs
Number of variables by role
outcome: 1
predictor: 10
-- Training information
Training data contained 32 data points and no incomplete rows.
-- Operations
* Sparse, unbalanced variable filter removed: <none> | Trained
Code
print(rec)
Message
-- Recipe ----------------------------------------------------------------------
-- Inputs
Number of variables by role
outcome: 1
predictor: 4
-- Operations
* Sparse, unbalanced variable filter on: x1, x2, x3, x4
Code
prep(rec)
Message
-- Recipe ----------------------------------------------------------------------
-- Inputs
Number of variables by role
outcome: 1
predictor: 4
-- Training information
Training data contained 50 data points and no incomplete rows.
-- Operations
* Sparse, unbalanced variable filter removed: x3 and x4 | Trained
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