tfdatasets (version 2.17.0)

step_categorical_column_with_vocabulary_list: Creates a categorical column specification

Description

Creates a categorical column specification

Usage

step_categorical_column_with_vocabulary_list(
  spec,
  ...,
  vocabulary_list = NULL,
  dtype = NULL,
  default_value = -1L,
  num_oov_buckets = 0L
)

Value

a FeatureSpec object.

Arguments

spec

A feature specification created with feature_spec().

...

Comma separated list of variable names to apply the step. selectors can also be used.

vocabulary_list

An ordered iterable defining the vocabulary. Each feature is mapped to the index of its value (if present) in vocabulary_list. Must be castable to dtype. If NULL the vocabulary will be defined as all unique values in the dataset provided when fitting the specification.

dtype

The type of features. Only string and integer types are supported. If NULL, it will be inferred from vocabulary_list.

default_value

The integer ID value to return for out-of-vocabulary feature values, defaults to -1. This can not be specified with a positive num_oov_buckets.

num_oov_buckets

Non-negative integer, the number of out-of-vocabulary buckets. All out-of-vocabulary inputs will be assigned IDs in the range [lenght(vocabulary_list), length(vocabulary_list)+num_oov_buckets) based on a hash of the input value. A positive num_oov_buckets can not be specified with default_value.

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_identity(), step_categorical_column_with_vocabulary_file(), step_crossed_column(), step_embedding_column(), step_indicator_column(), step_numeric_column(), step_remove_column(), step_shared_embeddings_column(), steps

Examples

if (FALSE) {
library(tfdatasets)
data(hearts)
hearts <- tensor_slices_dataset(hearts) %>% dataset_batch(32)

# use the formula interface
spec <- feature_spec(hearts, target ~ thal) %>%
  step_categorical_column_with_vocabulary_list(thal)

spec_fit <- fit(spec)
final_dataset <- hearts %>% dataset_use_spec(spec_fit)
}