Description
Return additional true negatives needed for a specificity target.
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 additional true negatives needed for a specificity target.
When to use this tool
Use Binary Specificity Minimum Count Margin when checking the stated confusion-count, metric contribution or abstention-denominator convention.
How to use the tool and how it works
- Enter trueNegative, falsePositive, requiredSpecificity. Use the units and conventions below.
- Run the tool. Correct any format, range, or cross-field input error before interpreting the output.
- Read minimumTrueNegative, additionalNeeded. Use the output convention below.
Return additional true negatives needed for a specificity target. Require nonnegative whole TN/FP and requiredSpecificity in [0,1]; minimumTN = ceil((TN+FP)*target), additionalNeeded = max(0,minimumTN-TN).1
| Input field | Meaning and units | Accepted input |
|---|---|---|
| trueNegative | True Negative | Required. Safe integer; minimum 0. |
| falsePositive | False Positive | Required. Safe integer; minimum 0. |
| requiredSpecificity | Required Specificity | Required. Finite number; minimum 0; maximum 1. |
| Output field | Interpretation | Returned shape |
|---|---|---|
| minimumTrueNegative | Minimum True Negative | Required. Safe integer. |
| additionalNeeded | Additional Needed | Required. Safe integer. |
{
"input": {
"trueNegative": 6,
"falsePositive": 4,
"requiredSpecificity": 0.8
},
"output": {
"minimumTrueNegative": 8,
"additionalNeeded": 2
}
}Limitations and assumptions
- Support is held fixed; zero negatives yields zero need without a defined observed specificity.
- 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
- Class Recall Minimum Count Margin
Return additional true positives needed for a recall target at fixed support.
- Binary Abstention Coverage Count
Return acceptance coverage from positive, negative and abstained counts.