This document describes the ML.MULTI_HOT_ENCODER function, which lets you encode a string array expression by using a multi-hot encoding scheme.

The encoding vocabulary is sorted alphabetically. NULL values and categories that aren't in the vocabulary are encoded with an index value of 0.

When used in the TRANSFORM clause, the vocabulary calculated during training, along with the top k and frequency threshold values that you specified, are automatically used in prediction.


ML.MULTI_HOT_ENCODER(array_expression [, top_k] [, frequency_threshold]) OVER()


ML.MULTI_HOT_ENCODER takes the following arguments:

  • array_expression: the ARRAY<STRING> expression to encode.
  • top_k: an INT64 value that specifies the number of categories included in the encoding vocabulary. The function selects the top_k most frequent categories in the data and uses those; categories below this threshold are encoded to 0. This value must be less than 1,000,000 to avoid problems due to high dimensionality. The default value is 32,000.
  • frequency_threshold: an INT64 value that limits the categories included in the encoding vocabulary based on category frequency. The function uses categories whose frequency is greater than or equal to frequency_threshold; categories below this threshold are encoded to 0. The default value is 5.


ML.MULTI_HOT_ENCODER returns an array of struct values in the form ARRAY<STRUCT<INT64, FLOAT64>>. The first element in the struct provides the index of the encoded string expression, and the second element provides the value of the encoded string expression.


The following example performs multi-hot encoding on a set of string array expressions. It limits the encoding vocabulary to the three categories that occur the most frequently in the data and that also occur one or more times.

SELECT f[OFFSET(0)] AS f0, ML.MULTI_HOT_ENCODER(f, 3, 1) OVER () AS output
    SELECT ['a', 'b', 'b', 'c', NULL] AS f
    SELECT ['c', 'c', 'd', 'd', NULL] AS f

The output looks similar to the following:

|  f0  | output.index | output.value |
|  a   |  1           |  1.0         |
|      |  2           |  1.0         |
|      |  3           |  1.0         |
|      |  0           |  1.0         |
|  c   |  3           |  1.0         |
|      |  0           |  1.0         |

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