Description
Center and rescale one feature with a supplied origin and unit factor.
Data workflows require explicit training scope, feature/label availability, missingness codes, group assignments and evaluation direction. Supplied training statistics are not proof that preprocessing avoided leakage. A local target-encoding term or retransformed prediction depends on assumptions that must be checked in the complete model and validation design.
Center and rescale one feature with a supplied origin and unit factor.
When to use this tool
Use Feature Unit Reference Offset when you already have featureValue, referenceOrigin, unitsPerOutputUnit and need to center and rescale one feature with a supplied origin and unit factor.
How to use the tool and how it works
- Enter featureValue, referenceOrigin, unitsPerOutputUnit. Use the units and conventions below.
- Run the tool. Correct any format, range, or cross-field input error before interpreting the output.
- Read transformedValue. Use the output convention below.
Require unitsPerOutputUnit>0; return (featureValue-referenceOrigin)/unitsPerOutputUnit.1
| Input field | Meaning and units | Accepted input |
|---|---|---|
| featureValue | Feature Value | Required. Finite number. |
| referenceOrigin | Reference Origin | Required. Finite number. |
| unitsPerOutputUnit | Positive source units per output unit; divide after subtracting the source-unit origin. | Required. Finite number; strictly above 0. |
| Output field | Interpretation | Returned shape |
|---|---|---|
| transformedValue | Transformed Value | Required. Finite number. |
{
"input": {
"featureValue": 150,
"referenceOrigin": 100,
"unitsPerOutputUnit": 10
},
"output": {
"transformedValue": 5
}
}Limitations and assumptions
- The factor is source units per output unit. No physical units, reference, training statistics, missing-value handling or preprocessing validity is inferred.
- 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
Review the full data lineage, preprocessing fit, split design and evaluation procedure for model conclusions. Estimate required statistics only within the intended training folds and verify actual availability; local supplied-value transformations cannot establish those properties by themselves.
References
Similar or alternative tools
- Train Only Scaler Single Value Apply
Apply a supplied training-center and scale to one value.
- Regression Coefficient Unit Rescale
Rescale a supplied regression coefficient between predictor and outcome units.