Description
Measure a supplied upper-minus-lower ordinal-threshold gap.
Classification terms depend on label vocabularies, decision thresholds and denominator definitions. One class recall is not a full balanced-accuracy metric, and a row or column total is not automatically a precision or recall denominator. Empty or zero-total cases need an explicit defined flag or convention.
Measure a supplied upper-minus-lower ordinal-threshold gap.
When to use this tool
Use Ordinal Label Adjacent Threshold Gap when you already have lowerThreshold, upperThreshold and need to measure a supplied upper-minus-lower ordinal-threshold gap.
How to use the tool and how it works
- Enter lowerThreshold, upperThreshold. Use the units and conventions below.
- Run the tool. Correct any format, range, or cross-field input error before interpreting the output.
- Read signedGap. Use the output convention below.
Return upperThreshold-lowerThreshold without requiring order.1
| Input field | Meaning and units | Accepted input |
|---|---|---|
| lowerThreshold | Lower Threshold | Required. Finite number. |
| upperThreshold | Upper Threshold | Required. Finite number. |
| Output field | Interpretation | Returned shape |
|---|---|---|
| signedGap | upperThreshold-lowerThreshold, retaining a negative gap instead of enforcing ordinal order. | Required. Finite number. |
{
"input": {
"lowerThreshold": 12,
"upperThreshold": 17
},
"output": {
"signedGap": 5
}
}Limitations and assumptions
- Negative gaps are retained. No threshold fit, ordinal model, calibrated probability or valid class ordering is established.
- 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
Evaluate the complete prediction set, confusion structure and decision policy. Report missingness, class scope and uncertainty with the full metric; local threshold flags or one-cell fractions cannot characterize overall model performance.
References
Similar or alternative tools
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