Description
Compare precision and recall under a supplied tolerance.
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.
Compare precision and recall under a supplied tolerance.
When to use this tool
Use Precision Recall Breakeven Residual when checking the stated confusion-count, metric contribution or abstention-denominator convention.
How to use the tool and how it works
- Enter precision, recall, tolerance. Use the units and conventions below.
- Run the tool. Correct any format, range, or cross-field input error before interpreting the output.
- Read residual, equalWithinTolerance. Inspect equalWithinTolerance before interpreting the associated values.
Compare precision and recall under a supplied tolerance. Require both in [0,1] and tolerance >= 0; residual = precision-recall, equalWithinTolerance uses abs(residual) <= tolerance.1
| Input field | Meaning and units | Accepted input |
|---|---|---|
| precision | Precision | Required. Finite number; minimum 0; maximum 1. |
| recall | Recall | Required. Finite number; minimum 0; maximum 1. |
| tolerance | Nonnegative caller-selected comparison tolerance, in matching units. | Required. Finite number; minimum 0. |
| Output field | Interpretation | Returned shape |
|---|---|---|
| residual | Signed difference in the direction stated above, with matching units. | Required. Finite number. |
| equalWithinTolerance | Equal Within Tolerance | Required. Boolean. |
{
"input": {
"precision": 0.75,
"recall": 0.5,
"tolerance": 0.1
},
"output": {
"residual": 0.25,
"equalWithinTolerance": false
}
}Limitations and assumptions
- This does not locate a precision-recall curve breakeven or establish statistical equivalence.
- 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
Similar or alternative tools
- Classification: Precision Zero Denominator Policy
Return precision with an explicit zero-denominator report policy.
- Class Recall Minimum Count Margin
Return additional true positives needed for a recall target at fixed support.