column_categorical_weighted {tfestimators} | R Documentation |
Construct a Weighted Categorical Column
Description
Use this when each of your sparse inputs has both an ID and a value. For example, if you're representing text documents as a collection of word frequencies, you can provide 2 parallel sparse input features ('terms' and 'frequencies' below).
Usage
column_categorical_weighted(
categorical_column,
weight_feature_key,
dtype = tf$float32
)
Arguments
categorical_column |
A categorical column created by
|
weight_feature_key |
String key for weight values. |
dtype |
Type of weights, such as |
Value
A categorical column composed of two sparse features: one represents id, the other represents weight (value) of the id feature in that example.
Raises
ValueError: if
dtype
is not convertible to float.
See Also
Other feature column constructors:
column_bucketized()
,
column_categorical_with_hash_bucket()
,
column_categorical_with_identity()
,
column_categorical_with_vocabulary_file()
,
column_categorical_with_vocabulary_list()
,
column_crossed()
,
column_embedding()
,
column_numeric()
,
input_layer()