library(tfdatasets)
data(hearts)
<- tempfile()
file writeLines(unique(hearts$thal), file)
<- tensor_slices_dataset(hearts) %>% dataset_batch(32)
hearts
# use the formula interface
<- feature_spec(hearts, target ~ age) %>%
spec step_numeric_column(age) %>%
step_bucketized_column(age, boundaries = c(10, 20, 30))
<- fit(spec)
spec_fit <- hearts %>% dataset_use_spec(spec_fit) final_dataset
step_crossed_column
Creates crosses of categorical columns
Description
Use this step to create crosses between categorical columns.
Usage
step_crossed_column(spec, ..., hash_bucket_size, hash_key = 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. |
hash_bucket_size | An int > 1. The number of buckets. |
hash_key | (optional) Specify the hash_key that will be used by the FingerprintCat64 function to combine the crosses fingerprints on SparseCrossOp. |
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_identity()
, step_categorical_column_with_vocabulary_file()
, step_categorical_column_with_vocabulary_list()
, step_embedding_column()
, step_indicator_column()
, step_numeric_column()
, step_remove_column()
, step_shared_embeddings_column()
, steps