The ML.MAX_ABS_SCALER function

This document describes theML.MAX_ABS_SCALER function, which lets youscale a numerical expression to the range[-1, 1] by dividing with the maximum absolute value. It doesn'tshift or center the data, and so doesn't destroy any sparsity.

When used in theTRANSFORM clause,the maximum absolute value calculated during training is automaticallyused in prediction.

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.MAX_ABS_SCALER(numerical_expression) OVER()

Arguments

ML.MAX_ABS_SCALER takes the following argument:

• numerical_expression: thenumericalexpression to scale.

Output

ML.MAX_ABS_SCALER returns aFLOAT64 value that represents the scalednumerical expression.

Example

The following example scales a set of numerical expressions to have valuesbetween-1 and1:

SELECTf,ML.MAX_ABS_SCALER(f)OVER()ASoutputFROMUNNEST([NULL,-3,1,2,3,4,5])ASfORDERBYf;

The output looks similar to the following:

+------+--------+|  f   | output |+------+--------+| NULL |   NULL ||   -3 |   -0.6 ||    1 |    0.2 ||    2 |    0.4 ||    3 |    0.6 ||    4 |    0.8 ||    5 |    1.0 |+------+--------+

What's next

• For information about feature preprocessing, seeFeature preprocessing overview.