Description
Return a Bayes probability threshold and cost ratio.
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 a Bayes probability threshold and cost ratio.
When to use this tool
Use Classification: Decision Threshold To Cost Ratio when comparing the stated classification, rejection or utility terms under supplied assumptions.
How to use the tool and how it works
- Enter falsePositiveCost, falseNegativeCost. 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.
Return a Bayes probability threshold and cost ratio. Require falsePositiveCost/falseNegativeCost > 0; threshold = FPcost/(FPcost+FNcost), ratio = FPcost/FNcost.1
| Input field | Meaning and units | Accepted input |
|---|---|---|
| falsePositiveCost | False Positive Cost | Required. Finite number. |
| falseNegativeCost | False Negative Cost | Required. Finite number. |
| Output field | Interpretation | Returned shape |
|---|---|---|
| result | Returned calculated value or nested object under the stated output convention. | Required. Object. |
| result.bayesProbabilityThreshold | Bayes Probability Threshold | Calculated result member: number. |
| result.falsePositiveToFalseNegativeCostRatio | False Positive To False Negative Cost Ratio | Calculated result member: number. |
{
"input": {
"falsePositiveCost": 2,
"falseNegativeCost": 8
},
"output": {
"result": {
"bayesProbabilityThreshold": 0.2,
"falsePositiveToFalseNegativeCostRatio": 0.25
}
}
}Limitations and assumptions
- This assumes zero correct-classification costs and a suitable posterior probability; actual costs and policy are supplied.
- 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
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.
- Binary Rejection Cost Indifference
Return expected positive, negative and reject risks.