Feature Scaling Calculator

Scale raw feature values using min-max normalization, z-score standardization, robust scaling, and max-abs normalization for machine learning preprocessing.

Inputs

Raw Value

Minimum Value

Maximum Value

Mean

Standard Deviation

Tab to move between fields

Results

Min-Max Scaled Value

0.5

Z-Score (Standard Scaled)

Robust Scaled Value0

Max-Abs Normalized0.5

Feature Range100

Deviations from Mean0

How to Use This Calculator

Enter the feature values or paste summary statistics (min, max, mean, std).
Select the scaling method: standardization (Z-score), min-max normalization, or robust scaling.
Review scaled feature range and distribution.
Use standardization for distance-based algorithms (KNN, SVM) and min-max for neural networks.
Always fit scaling parameters on training data only -- transform test data using training parameters.

How the result changes with Maximum Value

Maximum Value	Min-Max Scaled Value	Z-Score (Standard Scaled)
-800,000	-0	0
-300,000	-0	0
300,000	0	0
800,000	0	0

What each input means

Raw Value: The original unscaled feature value you want to transform.
Minimum Value: The minimum observed value in your feature column.
Maximum Value: The maximum observed value in your feature column.
Mean: The arithmetic mean (average) of your feature column.
Standard Deviation: The standard deviation of your feature column. Used for z-score standardization.

What each result means

Min-Max Scaled Value: Value scaled to [0, 1] range using (x - min) / (max - min).
Z-Score (Standard Scaled): Number of standard deviations from the mean: (x - mean) / std.
Robust Scaled Value: Scaled using range instead of std dev, less sensitive to outliers.
Max-Abs Normalized: Value divided by the maximum absolute value in the range.

How this is calculated

Worked example, using the default values

Identify Input Parameters
4 parameters
Raw Value = 50, Minimum Value = 0, Maximum Value = 100, Mean = 50 = 5 input(s) provided
Calculate Min-Max Scaled Value
Min-Max Scaled Value
0.5 = 0.5
Calculate Z-Score
Z-Score
0 = 0
Calculate Robust Scaled Value
Robust Scaled Value
0 = 0
Calculate Max-Abs Normalized
Max-Abs Normalized
0.5 = 0.5

Engine last updated July 28, 2026. Checked against 1 independently-derived test — how we verify calculators.

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