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_hash_bucket(thal, hash_bucket_size = 3)
spec_fit <- fit(spec)
final_dataset <- hearts %>% dataset_use_spec(spec_fit) step_categorical_column_with_hash_bucket
Creates a categorical column with hash buckets specification
Description
Represents sparse feature where ids are set by hashing.
Usage
step_categorical_column_with_hash_bucket(
spec,
...,
hash_bucket_size,
dtype = tf$string
) 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. |
| hash_bucket_size | An int > 1. The number of buckets. |
| dtype | The type of features. Only string and integer types are supported. |
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_identity(), 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