Use this normalization to put numeric features on a defined scale before comparison, visualization, or algorithms sensitive to magnitude.

Values

Required list input.

Target minimum

Optional number input.

Target maximum

Optional number input.

Scale a numeric dataset to a requested inclusive range. The tool evaluates the supplied inputs together and returns the named outputs below; it does not infer omitted operating conditions or change the units shown.^[1]

Normalized values

The resulting normalized values returned as a list.

Source minimum

The resulting source minimum returned as a number.

Source maximum

The resulting source maximum returned as a number.

• Scaling parameters must be learned from the appropriate training or reference population. Constant features, outliers, missing values, leakage, distribution shift, and inverse transformation require explicit policies.
• Use finite inputs in the displayed units and preserve more precision than the final presentation requires. Independently verify safety-critical, financial, compliance, or production decisions.

Store the fitted parameters, apply them unchanged to later data, inspect distributions, and compare robust scaling when outliers dominate.

• Standardize Dataset Tool

  Standardize a numeric dataset to population z-scores.

• Numeric Dataset Parser

  Parse and normalize a list of finite numeric values.

• Vector Normalization Calculator

  Normalize a nonzero numeric vector to unit Euclidean magnitude.