Fit Feature Scaler Node

F

AI/ML/Preprocessing

Learn per-feature offsets and scales from a training table. Distance- and gradient-based models (Logistic Regression, Elastic Net, SVM, KNN, Gaussian Mixture) only behave when their features share a scale.

fit_feature_scalerml

Inputs5

Outputs4

Security exposure7/10

Packageml

Ratings

Scores range from 0 to 10. Higher values mean more impact, exposure, or operational weight.

SecurityAttack surface and exposure impact.

7/10High

PrivacyPotential sensitivity of processed data.

6/10Medium

PerformanceRuntime or resource pressure.

8/10High

GovernancePolicy, audit, or compliance impact.

7/10High

ReliabilityOperational stability considerations.

8/10High

CostExternal or compute cost impact.

8/10High

Input Pins

5

Input

Execution

exec_in

Execution trigger that begins fitting the scaler

Data Source

String

source

Choose which backend supplies the training data

Default Database

Database

Method

String

method

Standard centers each feature and divides it by its standard deviation. MinMax squeezes each feature into the Min..Max range. MaxAbs divides each feature by its largest absolute value, keeping zeros at zero.

Default Standard

StandardMinMaxMaxAbs

Min

Float

min

Lower bound of the target range. Only read when Method is MinMax.

Default 0

Max

Float

max

Upper bound of the target range. Only read when Method is MinMax.

Default 1

Output Pins

4

Done

Execution

exec_out

Activated once the scaler is fitted

Model

Struct

model

Thread-safe handle to the fitted scaler. Feed it to Apply Transform to scale any table with these statistics.

SchemaNodeMLModelNodeMLModelNodeMLModel1 fields

model_refstringrequired

Schema enforced

Offsets

Float Array

offsets

Value subtracted from each feature before scaling: the mean for Standard, the minimum for MinMax, zero for MaxAbs

Scales

Float Array

scales

Multiplier applied to each feature. linfa stores the reciprocal, so this is 1/std for Standard and 1/(max-min) for MinMax, and it stays 1 for constant features.

Node Info

Internal name

fit_feature_scaler

Category

AI/ML/Preprocessing