library(tfdatasets)
data(hearts)
file <- tempfile()
writeLines(unique(hearts$thal), file)
hearts <- tensor_slices_dataset(hearts) %>% dataset_batch(32)
# use the formula interface
spec <- feature_spec(hearts, target ~ age) %>%
step_numeric_column(age) %>%
step_bucketized_column(age, boundaries = c(10, 20, 30))
spec_fit <- fit(spec)
final_dataset <- hearts %>% dataset_use_spec(spec_fit) 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