The ML.NORMALIZER function

This document describes theML.NORMALIZER function, which lets you normalizean array of numerical expressions using a givenp-norm.

You can use this function with models that supportmanual feature preprocessing. For moreinformation, see the following documents:

• End-to-end user journeys for ML models
• Contribution analysis user journey

Syntax

ML.NORMALIZER(array_expression [, p])

Arguments

ML.NORMALIZER takes the following arguments:

• array_expression: an array ofnumericalexpressions to normalize.
• p: aFLOAT64 value that specifies the degree of p-norm. Thiscan be0.0, any value greater than or equal to1.0, orCAST('+INF' AS FLOAT64). The default value is2.

Output

ML.NORMALIZER returns an array ofFLOAT64 values that represent thenormalized numerical expressions.

Example

The following example normalizes a set of numerical expressions using a p-normof2:

SELECTML.NORMALIZER([4.0,1.0,2.0,2.0,0.0])ASoutput;

The output looks similar to the following:

+--------+| output |+--------+| 0.8    || 0.2    || 0.4    || 0.4    || 0.0    |+--------+

What's next

• For information about feature preprocessing, seeFeature preprocessing overview.