Description
Return utility indifference probability for positive prediction.
A classification decision can compare expected losses or utilities under supplied probabilities and outcome costs. The resulting threshold depends on which outcomes are charged, the cost signs and whether abstention is allowed; arithmetic alone does not establish appropriate costs or reliable probabilities.
Return utility indifference probability for positive prediction.
When to use this tool
Use Threshold Utility Indifference Probability when comparing the stated classification, rejection or utility terms under supplied assumptions.
How to use the tool and how it works
- Enter truePositiveGain, falsePositiveCost. Use the units and conventions below.
- Run the tool. Correct any format, range, or cross-field input error before interpreting the output.
- Read threshold. Use the output convention below.
Return utility indifference probability for positive prediction. Require nonnegative truePositiveGain/falsePositiveCost with positive sum; threshold = cost/(gain+cost).1
| Input field | Meaning and units | Accepted input |
|---|---|---|
| truePositiveGain | True Positive Gain | Required. Finite number; minimum 0. |
| falsePositiveCost | False Positive Cost | Required. Finite number; minimum 0. |
| Output field | Interpretation | Returned shape |
|---|---|---|
| threshold | Threshold | Required. Finite number. |
{
"input": {
"truePositiveGain": 3,
"falsePositiveCost": 1
},
"output": {
"threshold": 0.25
}
}Limitations and assumptions
- This assumes the stated two-outcome utility comparison and a suitable probability; no full decision problem or cost model is validated.
- 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
Specify the full decision problem and validate probabilities and outcome costs before using a threshold; assess performance and consequences on relevant data.
References
Similar or alternative tools
- Abstention Cost Indifference Threshold
Return correct-probability indifference between classification and abstention.
- Classification: Decision Threshold To Cost Ratio
Return a Bayes probability threshold and cost ratio.