The ML.STANDARD_SCALER function

This document describes the ML.STANDARD_SCALER function, which lets you scale a numerical expression by using z-score.

When used in the TRANSFORM clause, the standard deviation and mean values calculated to standardize the expression are automatically used in prediction.

You can use this function with models that support manual feature preprocessing. For more information, see the following documents:

Syntax

ML.STANDARD_SCALER(numerical_expression) OVER()

Arguments

ML.STANDARD_SCALER takes the following argument:

  • numerical_expression: the numerical expression to scale.

Output

ML.STANDARD_SCALER returns a FLOAT64 value that represents the scaled numerical expression.

Example

The following example scales a set of numerical expressions to have a mean of 0 and standard deviation of 1:

SELECT
  f, ML.STANDARD_SCALER(f) OVER() AS output
FROM
  UNNEST([1,2,3,4,5]) AS f;

The output looks similar to the following:

+---+---------------------+
| f |       output        |
+---+---------------------+
| 1 | -1.2649110640673518 |
| 5 |  1.2649110640673518 |
| 2 | -0.6324555320336759 |
| 4 |  0.6324555320336759 |
| 3 |                 0.0 |
+---+---------------------+

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