Description
Round one binary probability with an explicit half tie.
Classification scores rank labels or locate a prediction relative to a chosen decision boundary. Raw scores and logits need not be calibrated probabilities; exact ties, score direction and inclusion of boundary values are separate policy choices that can change the reported decision.
Round one binary probability with an explicit half tie.
When to use this tool
Use Classification: Binary Probability Rounding Tie when checking the stated score comparison, tie or decision-band policy.
How to use the tool and how it works
- Enter probability, tiePolicy. Use the units and conventions below.
- Run the tool. Correct any format, range, or cross-field input error before interpreting the output.
- Read result. Expand result to inspect the returned fields.
Round one binary probability with an explicit half tie. Require p in [0,1] and positive/negative policy; classIndex is zero below 0.5, one above, and follows policy at exact equality; tie reports equality.1
| Input field | Meaning and units | Accepted input |
|---|---|---|
| probability | Probability | Required. Finite number. |
| tiePolicy | Tie Policy | Required. Text; one of "positive", "negative". Implementation limit: 8192 Unicode code points and 16384 UTF-16 code units. |
| Output field | Interpretation | Returned shape |
|---|---|---|
| result | Returned calculated value or nested object under the stated output convention. | Required. Object. |
| result.classIndex | Class Index | Calculated result member: number. |
| result.tie | Tie | Calculated result member: boolean. |
{
"input": {
"probability": 0.5,
"tiePolicy": "negative"
},
"output": {
"result": {
"classIndex": 0,
"tie": true
}
}
}Limitations and assumptions
- No tolerance, calibration or classification-performance guarantee is provided.
- Outputs are nested inside result. 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
Use a complete evaluation dataset and an explicit decision policy to assess performance; fit and validate calibration separately when a probability interpretation is required.
References
Similar or alternative tools
- Class Label Cost Tie Selector
Select a minimum-cost class under an explicit tie policy.
- Classifier Logit Tie Policy
Return maximal-logit indexes under a tie policy.