Which TensorFlow function can you use to configure a categorical column if you don't know all of the possible values for that column?

The correct answer is B. categorical_column_with_hash_bucket. Explanation/Reference: If you know the set of all possible feature values of a column and there are only a few of them, you can use categorical_column_with_vocabulary_list. Each key in the list will get assigned an auto-incremental ID starting from 0. What if we don't know the se

Submitted by deeparc· Mar 30, 2026Operationalizing machine learning models

Question

Which TensorFlow function can you use to configure a categorical column if you don't know all of the possible values for that column?

Options

Acategorical_column_with_vocabulary_list
Bcategorical_column_with_hash_bucket
Ccategorical_column_with_unknown_values
Dsparse_column_with_keys

How the community answered

(48 responses)

A
2% (1)
B
75% (36)
C
15% (7)
D
8% (4)

Explanation

Explanation/Reference: If you know the set of all possible feature values of a column and there are only a few of them, you can use categorical_column_with_vocabulary_list. Each key in the list will get assigned an auto-incremental ID starting from 0. What if we don't know the set of possible values in advance? Not a problem. We can use categorical_column_with_hash_bucket instead. What will happen is that each possible value in the feature column occupation will be hashed to an integer ID as we encounter them in training.

Topics

#TensorFlow#categorical features#hash bucket#feature columns

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