Description
Calculate a supplied confusion cell's row and column shares.
Classification terms depend on label vocabularies, decision thresholds and denominator definitions. One class recall is not a full balanced-accuracy metric, and a row or column total is not automatically a precision or recall denominator. Empty or zero-total cases need an explicit defined flag or convention.
Calculate a supplied confusion cell's row and column shares.
When to use this tool
Use Confusion Cell Row Share Column Share when you already have cellCount, rowTotal, columnTotal and need to calculate a supplied confusion cell's row and column shares.
How to use the tool and how it works
- Enter cellCount, rowTotal, columnTotal. Use the units and conventions below.
- Run the tool. Correct any format, range, or cross-field input error before interpreting the output.
- Read rowShare, columnShare. Use the output convention below.
Require positive safe row/column totals and nonnegative safe cell count<=each; return cell/row and cell/column.1
| Input field | Meaning and units | Accepted input |
|---|---|---|
| cellCount | Cell Count | Required. Safe integer; minimum 0. |
| rowTotal | Row Total | Required. Safe integer; minimum 1. |
| columnTotal | Column Total | Required. Safe integer; minimum 1. |
| Output field | Interpretation | Returned shape |
|---|---|---|
| rowShare | cellCount/rowTotal; the caller must determine whether this denominator represents recall or another share. | Required. Finite number. |
| columnShare | cellCount/columnTotal; not automatically precision without the relevant matrix orientation. | Required. Finite number. |
{
"input": {
"cellCount": 12,
"rowTotal": 20,
"columnTotal": 30
},
"output": {
"rowShare": 0.6,
"columnShare": 0.4
}
}Limitations and assumptions
- No row/column semantic orientation is assumed. These are not automatically precision or recall; no full confusion matrix, class or prediction is verified.
- 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 prediction set, confusion structure and decision policy. Report missingness, class scope and uncertainty with the full metric; local threshold flags or one-cell fractions cannot characterize overall model performance.
References
Similar or alternative tools
- Balanced Accuracy Single Class Term
Calculate one class's recall and contribution to balanced accuracy.
- Binary Predicted Label Count Balance
Sum supplied binary confusion cells into predicted-label totals.