Description
Apply a supplied training-center and scale to one value.
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.
Apply a supplied training-center and scale to one value.
When to use this tool
Use Train Only Scaler Single Value Apply when you already have value, suppliedTrainingCenter, suppliedTrainingScale and need to apply a supplied training-center and scale to one value.
How to use the tool and how it works
- Enter value, suppliedTrainingCenter, suppliedTrainingScale. Use the units and conventions below.
- Run the tool. Correct any format, range, or cross-field input error before interpreting the output.
- Read scaledValue. Use the output convention below.
Require suppliedTrainingScale positive/finite; return (value-suppliedTrainingCenter)/scale.1
| Input field | Meaning and units | Accepted input |
|---|---|---|
| value | Value | Required. Finite number. |
| suppliedTrainingCenter | Supplied Training Center | Required. Finite number. |
| suppliedTrainingScale | Positive supplied divisor; this tool neither fits nor verifies training-only statistics. | Required. Finite number; strictly above 0. |
| Output field | Interpretation | Returned shape |
|---|---|---|
| scaledValue | Scaled Value | Required. Finite number. |
{
"input": {
"value": 12,
"suppliedTrainingCenter": 10,
"suppliedTrainingScale": 2
},
"output": {
"scaledValue": 1
}
}Limitations and assumptions
- The center and scale are not estimated or verified as training-only. This arithmetic alone does not prevent leakage, handle missing values or establish a valid preprocessing pipeline.
- 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
- Feature Unit Reference Offset
Center and rescale one feature with a supplied origin and unit factor.
- Target Encoding Prior Single Level Term
Calculate one level's prior-smoothed target-encoding term.