step_categorical_column_with_identity: Create a categorical column with identity

In tfdatasets: Interface to 'TensorFlow' Datasets

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

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.

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

Examples

## Not run: 
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)

## End(Not run)

tfdatasets documentation built on Sept. 11, 2024, 8:53 p.m.