library(tfdatasets)
data(hearts)
hearts$thal <- as.integer(as.factor(hearts$thal)) - 1L
hearts <- tensor_slices_dataset(hearts) %>% dataset_batch(32)
# use the formula interface
spec <- feature_spec(hearts, target ~ thal) %>%
step_categorical_column_with_identity(thal, num_buckets = 5)
spec_fit <- fit(spec)
final_dataset <- hearts %>% dataset_use_spec(spec_fit) step_categorical_column_with_identity
Create a categorical column with identity
Description
Use this when your inputs are integers in the range [0-num_buckets).
Usage
step_categorical_column_with_identity(
spec,
...,
num_buckets,
default_value = NULL
) Arguments
| Arguments | Description |
|---|---|
| spec | A feature specification created with feature_spec(). |
| … | Comma separated list of variable names to apply the step. selectors can also be used. |
| num_buckets | Range of inputs and outputs is [0, num_buckets). |
| default_value | If NULL, this column’s graph operations will fail for out-of-range inputs. Otherwise, this value must be in the range [0, num_buckets), and will replace inputs in that range. |
Value
a FeatureSpec object.
Examples
See Also
steps for a complete list of allowed steps. Other Feature Spec Functions: dataset_use_spec(), feature_spec(), fit.FeatureSpec(), step_bucketized_column(), step_categorical_column_with_hash_bucket(), step_categorical_column_with_vocabulary_file(), step_categorical_column_with_vocabulary_list(), step_crossed_column(), step_embedding_column(), step_indicator_column(), step_numeric_column(), step_remove_column(), step_shared_embeddings_column(), steps