The ML.NORMALIZER function
This document describes the ML.NORMALIZER
function, which lets you normalize
an array of numerical expressions using a given
p-norm.
Syntax
ML.NORMALIZER(array_expression [, p])
Arguments
ML.NORMALIZER
takes the following arguments:
array_expression
: an array of numerical expressions to normalize.p
: aFLOAT64
value that specifies the degree of p-norm. This can be0.0
, any value greater than or equal to1.0
, orCAST('+INF' AS FLOAT64)
. The default value is2
.
Output
ML.NORMALIZER
returns an array of FLOAT64
values that represent the
normalized numerical expressions.
Example
The following example normalizes a set of numerical expressions using a p-norm
of 2
:
SELECT ML.NORMALIZER([4.0, 1.0, 2.0, 2.0, 0.0]) AS output;
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, see Feature preprocessing overview.
- For information about the supported SQL statements and functions for each model type, see End-to-end user journey for each model.