# No ISOmap 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 # ISOmap fails gracefully 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()`: ! `step_isomap` failed with error: Error : TridiagEigen: eigen decomposition failed # check_name() is used Code prep(rec, training = dat) Message Condition Error in `step_isomap()`: Caused by error in `bake()`: ! Name collision occured. The following variable names already exists: i Isomap1 # empty printing Code rec Message -- Recipe ---------------------------------------------------------------------- -- Inputs Number of variables by role outcome: 1 predictor: 10 -- Operations * Isomap approximation with: --- 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: | Trained # keep_original_cols - can prep recipes with it missing Code rec <- prep(rec) Message Condition Warning: 'keep_original_cols' was added to `step_isomap()` after this recipe was created. Regenerate your recipe to avoid this warning. # printing 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