Description
Return precision with an explicit zero-denominator report policy.
Classifier metrics count particular outcomes on a declared population and positive-label convention. Precision, recall and accepted-only measures use different denominators. A reporting value at an empty denominator is a policy choice, while one cell, derivative or contribution does not constitute a complete performance evaluation.
Return precision with an explicit zero-denominator report policy.
When to use this tool
Use Classification: Precision Zero Denominator Policy when checking the stated confusion-count, metric contribution or abstention-denominator convention.
How to use the tool and how it works
- Enter truePositive, falsePositive, zeroPolicy. 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 precision with an explicit zero-denominator report policy. Require bounded nonnegative whole TP/FP and policy zero or one; defined means TP+FP != 0, otherwise precision returns the selected value.1
Classifier metrics use different outcome supports and denominator conventions. A zero-denominator reporting policy does not supply missing observed outcomes.2
| Input field | Meaning and units | Accepted input |
|---|---|---|
| truePositive | True Positive | Required. Safe integer. Calculation range: 0 through 1000000, inclusive. |
| falsePositive | False Positive | Required. Safe integer. Calculation range: 0 through 1000000, inclusive. |
| zeroPolicy | Zero Policy | Required. Text; one of "zero", "one". 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.defined | False at TP+FP=0 under either zeroPolicy, including a reported precision of one. | Calculated result member: boolean. |
| result.precision | Precision | Calculated result member: number. |
{
"input": {
"truePositive": 0,
"falsePositive": 0,
"zeroPolicy": "zero"
},
"output": {
"result": {
"defined": false,
"precision": 0
}
}
}Limitations and assumptions
- A reported one at zero denominator remains defined false; this is a convention rather than observed perfect precision.
- 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
Evaluate the complete confusion table, relevant class supports and abstention coverage together; use suitable uncertainty and validation methods for conclusions about predictive performance.
References
-
Calculation and input contract: classification/precision-zero-denominator-policy — tool.io
-
Model evaluation: classification metrics — scikit-learn developers
Similar or alternative tools
- Abstention Zero Coverage Policy
Report coverage and accepted accuracy under a zero-coverage policy.
- Precision Recall Breakeven Residual
Compare precision and recall under a supplied tolerance.