Description
For minimum<maximum return reconstructed=minimum+normalized*(maximum-minimum) and residual=value-reconstructed.
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.
For minimum<maximum return reconstructed=minimum+normalized*(maximum-minimum) and residual=value-reconstructed.
When to use this tool
Use Minmax Inverse Parameter Consistency 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, normalized, minimum, maximum. Use the units and conventions below.
- Run the tool. Correct any format, range, or cross-field input error before interpreting the output.
- Read reconstructed, residual. Use the output convention below.
For minimum<maximum return reconstructed=minimum+normalized*(maximum-minimum) and residual=value-reconstructed.1
| Input field | Meaning and units | Accepted input |
|---|---|---|
| value | Supplied scalar or returned value under the stated operation. | Required. Finite number. |
| normalized | Scalar transformed under the stated formula and zero policy. | Required. Finite number. |
| minimum | Minimum | Required. Finite number. |
| maximum | Maximum | Required. Finite number. |
| Output field | Interpretation | Returned shape |
|---|---|---|
| reconstructed | Reconstructed | Required. Finite number. |
| residual | Signed supplied-minus-reconstructed discrepancy under the stated formula. | Required. Finite number. |
{
"input": {
"value": 7,
"normalized": 0.5,
"minimum": 2,
"maximum": 10
},
"output": {
"reconstructed": 6,
"residual": 1
}
}Limitations and assumptions
- Normalized is not restricted to [0,1] and residual uses value-minus-reconstructed sign. This checks a supplied min-max relation without fitting bounds, choosing a tolerance, or declaring a transform accurate.
- 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
- Minmax Output Range Inversion
Return value=inputMinimum+(normalized-outputMinimum)/(outputMaximum-outputMinimum)*(inputMaximum-inputMinimum).
- Minmax Constant Column Output Policy
When equal, require value==minimum and return normalized=constantOutput and constant=true; otherwise return (value-minimum)/(maximum-minimum) and constant=false.