Description
When equal, require value==minimum and return normalized=constantOutput and constant=true; otherwise return (value-minimum)/(maximum-minimum) and constant=false.
Normalization depends on the supplied center, scale, norm, range, reference distribution, or denominator. A zero spread and a missing denominator need an explicit policy, and clipping differs from fitting a scaler. Evaluating one scalar or derivative term does not estimate every parameter or establish a distributional improvement.
When equal, require value==minimum and return normalized=constantOutput and constant=true; otherwise return (value-minimum)/(maximum-minimum) and constant=false.
When to use this tool
Use Minmax Constant Column Output Policy when you already have the required normalization parameters and need this local scalar, range, policy, or derivative term.
How to use the tool and how it works
- Enter value, minimum, maximum, constantOutput. Use the units and conventions below.
- Run the tool. Correct any format, range, or cross-field input error before interpreting the output.
- Read normalized, constant. Inspect constant before interpreting the associated values.
Require minimum<=maximum. When equal, require value==minimum and return normalized=constantOutput and constant=true; otherwise return (value-minimum)/(maximum-minimum) and constant=false.1
| Input field | Meaning and units | Accepted input |
|---|---|---|
| value | Supplied scalar or returned value under the stated operation. | Required. Finite number. |
| minimum | Minimum | Required. Finite number. |
| maximum | Maximum | Required. Finite number. |
| constantOutput | Arbitrary supplied fallback for a consistent constant column. | Required. Finite number. |
| Output field | Interpretation | Returned shape |
|---|---|---|
| normalized | Scalar transformed under the stated formula and zero policy. | Required. Finite number. |
| constant | Constant | Required. Boolean. |
{
"input": {
"value": 3,
"minimum": 3,
"maximum": 3,
"constantOutput": 0.5
},
"output": {
"normalized": 0.5,
"constant": true
}
}Limitations and assumptions
- ConstantOutput is a caller-selected fallback rather than an inferred normalized value. Nonconstant inputs may lie outside the stated range and are not clipped; no feature range or constant-column status is estimated from a dataset.
- Inputs must satisfy both the field types and the cross-field conditions above. Invalid input causes an error; a successful false flag or documented placeholder is a different result.
- Numeric calculations use binary floating point unless exact decimal-integer arithmetic is explicitly stated. No hidden measurement tolerance or decimal rounding is added; nonfinite or out-of-contract results are rejected. Numeric signed-zero results are exported as zero.
Alternative or Complementary methods
Fit or verify the intended scaler parameters and statistical model separately. Check units, zero policies, missingness, clipping, inverse conventions, and whether supplied norms or denominators belong to the same data.
References
Similar or alternative tools
- Normalization: Robust Scaler Zero Spread Policy
Compute one robust-reference normalized scalar with an explicit reject/zero policy for a supplied zero spread, preserving defined status.
- Feature Range Minmax Explicit Tolerance
Return span=maximum-minimum and degenerate=(span<=tolerance).