Returns a column for performing crosses of categorical features. Crossed
features will be hashed according to hash_bucket_size.
column_crossed(keys, hash_bucket_size, hash_key = NULL)An iterable identifying the features to be crossed. Each element can be either:
string: Will use the corresponding feature which must be of string type.
categorical column: Will use the transformed tensor produced by this column. Does not support hashed categorical columns.
The number of buckets (> 1).
Optional: specify the hash_key that will be used by the
FingerprintCat64 function to combine the crosses fingerprints on
SparseCrossOp.
A crossed column.
ValueError: If len(keys) < 2.
ValueError: If any of the keys is neither a string nor categorical column.
ValueError: If any of the keys is _HashedCategoricalColumn.
ValueError: If hash_bucket_size < 1.
Other feature column constructors: column_bucketized,
column_categorical_weighted,
column_categorical_with_hash_bucket,
column_categorical_with_identity,
column_categorical_with_vocabulary_file,
column_categorical_with_vocabulary_list,
column_embedding,
column_numeric, input_layer