The ML.MAX_ABS_SCALER function

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

When used in the TRANSFORM clause , the maximum absolute value calculated during training is automatically used in prediction.

You can use this function with models that support manual feature preprocessing . For more information, 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 : the numerical expression to scale.

Output

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

Example

The following example scales a set of numerical expressions to have values between -1 and 1 :

 SELECT 
  
 f 
 , 
  
 ML 
 . 
 MAX_ABS_SCALER 
 ( 
 f 
 ) 
  
 OVER 
  
 () 
  
 AS 
  
 output 
 FROM 
  
 UNNEST 
 ([ 
 NULL 
 , 
  
 - 
 3 
 , 
  
 1 
 , 
  
 2 
 , 
  
 3 
 , 
  
 4 
 , 
  
 5 
 ]) 
  
 AS 
  
 f 
 ORDER 
  
 BY 
  
 f 
 ; 

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, see Feature preprocessing overview .