Description
Sum weights with missing=false into retainedWeight and those with missing=true into excludedWeight.
Normalization depends on the supplied center, scale, norm, range, reference distribution, or denominator. A zero spread and a missing denominator need an explicit policy, and clipping differs from fitting a scaler. Evaluating one scalar or derivative term does not estimate every parameter or establish a distributional improvement.
Sum weights with missing=false into retainedWeight and those with missing=true into excludedWeight.
When to use this tool
Use Masked Scaler Denominator Adjustment when you already have the required normalization parameters and need this local scalar, range, policy, or derivative term.
How to use the tool and how it works
- Enter weights, missing. Keep parallel arrays aligned. Use the units and conventions below.
- Run the tool. Correct any format, range, or cross-field input error before interpreting the output.
- Read retainedWeight, excludedWeight. Use the output convention below.
Require aligned nonnegative weights and missing flags. Sum weights with missing=false into retainedWeight and those with missing=true into excludedWeight.1
| Input field | Meaning and units | Accepted input |
|---|---|---|
| weights | Weights | Required. Array of finite number; maximum items 256. |
| missing | Missing | Required. Array of boolean; maximum items 256. |
| Output field | Interpretation | Returned shape |
|---|---|---|
| retainedWeight | Retained Weight | Required. Finite number. |
| excludedWeight | Excluded Weight | Required. Finite number. |
{
"input": {
"weights": [
2,
3,
5
],
"missing": [
false,
true,
false
]
},
"output": {
"retainedWeight": 7,
"excludedWeight": 3
}
}Limitations and assumptions
- Only denominator components are returned, with zeros allowed. The tool does not validate missingness, renormalize a row, impute observations, or choose a statistical weighting model.
- 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
Fit or verify the intended scaler parameters and statistical model separately. Check units, zero policies, missingness, clipping, inverse conventions, and whether supplied norms or denominators belong to the same data.
References
Similar or alternative tools
- Row Standardization One Missing Denominator
For nonnegative sumSquares and integer 0<=missing<=count set denominator=count-missing minus one if sample.
- Rowwise Normalization Selected Cell
Return denominator=sum(row) and value=row[index]/denominator.