Code
print(im_rec)
Message
-- Recipe ----------------------------------------------------------------------
-- Inputs
Number of variables by role
predictor: 3
-- Training information
Training data contained 5 data points and no incomplete rows.
-- Operations
* Isomap was not conducted for: x1, x2, x3 | Trained
Code
recipe(Sepal.Length ~ ., data = iris) %>% step_bs(Sepal.Width, deg_free = 1,
degree = 1) %>% step_bs(Sepal.Length, deg_free = 1, degree = 1) %>%
step_other(Species, threshold = 1e-09) %>% step_isomap(all_numeric_predictors(),
num_terms = 1, neighbors = 1) %>% prep()
Message
Condition
Error in `step_isomap()`:
Caused by error in `prep()`:
x Failed with error:
i Error : TridiagEigen: eigen decomposition failed
Code
prep(rec, training = dat)
Message
Condition
Error in `step_isomap()`:
Caused by error in `bake()`:
! Name collision occurred. The following variable names already exist:
* `Isomap1`
Code
bake(im_trained, new_data = dat2[, 1:2])
Condition
Error in `step_isomap()`:
! The following required column is missing from `new_data`: x3.
Code
rec
Message
-- Recipe ----------------------------------------------------------------------
-- Inputs
Number of variables by role
outcome: 1
predictor: 10
-- Operations
* Isomap approximation with: <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
* Isomap approximation with: <none> | Trained
Code
rec <- prep(rec)
Message
Condition
Warning:
`keep_original_cols` was added to `step_isomap()` after this recipe was created.
i Regenerate your recipe to avoid this warning.
Code
print(rec)
Message
-- Recipe ----------------------------------------------------------------------
-- Inputs
Number of variables by role
predictor: 3
-- Operations
* Isomap approximation with: x1, x2, x3
Code
prep(rec)
Message
-- Recipe ----------------------------------------------------------------------
-- Inputs
Number of variables by role
predictor: 3
-- Training information
Training data contained 5 data points and no incomplete rows.
-- Operations
* Isomap approximation with: x1, x2, x3 | Trained
Code
recipe(~., data = mtcars) %>% step_isomap(all_predictors(), num_terms = 2,
neighbors = -1 / 3) %>% prep()
Condition
Error in `step_isomap()`:
Caused by error in `prep()`:
! `neighbors` must be a whole number, not the number -0.33.
Code
recipe(~., data = mtcars) %>% step_isomap(all_predictors(), prefix = NULL) %>%
prep()
Condition
Error in `step_isomap()`:
Caused by error in `prep()`:
! `prefix` must be a single string, not `NULL`.
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