library(tfdatasets)
data(hearts)
<- tensor_slices_dataset(hearts) %>% dataset_batch(32)
hearts
# use the formula interface
<- feature_spec(hearts, target ~ thal) %>%
spec step_categorical_column_with_hash_bucket(thal, hash_bucket_size = 3)
<- fit(spec)
spec_fit <- hearts %>% dataset_use_spec(spec_fit) final_dataset
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