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:

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

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 |
+---+---------------------+

What's next

• For information about feature preprocessing, see Feature preprocessing overview .