Description
Normalize nonnegative weights while recording original zero entries.
Normalization requires an explicit order of operations, center, scale and reference convention. Centering before scaling generally differs from subtracting the same center after scaling. A normalized weight or bounded uncertainty interval inherits supplied assumptions; zero entries, sentinel collisions and reference-category coding need separate interpretation.
Normalize nonnegative weights while recording original zero entries.
When to use this tool
Use Probability Vector Zero Entry Preserver when you already have weights and need to normalize nonnegative weights while recording original zero entries.
How to use the tool and how it works
- Enter weights. Use the units and conventions below.
- Run the tool. Correct any format, range, or cross-field input error before interpreting the output.
- Read normalized, zeroIndices. Use the output convention below.
Require nonnegative weights and at least one positive weight. Divide by the maximum, sum those scaled weights, then divide by that sum; zeroIndices lists original entries exactly equal to zero.1
| Input field | Meaning and units | Accepted input |
|---|---|---|
| weights | Weights | Required. Array of finite number; maximum items 256. |
| Output field | Interpretation | Returned shape |
|---|---|---|
| normalized | Normalized | Required. Array of finite number; maximum items 256. |
| zeroIndices | Zero-based positions whose original weights are exactly zero; excludes positive weights that underflow during normalization. | Required. Array of safe integer; maximum items 256. |
{
"input": {
"weights": [
0,
2,
6
]
},
"output": {
"normalized": [
0,
0.25,
0.75
],
"zeroIndices": [
0
]
}
}Limitations and assumptions
- Maximum scaling avoids overflow from a direct large sum, but tiny positive weights may underflow to zero without appearing in zeroIndices. Empty/all-zero lists are rejected.
- 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
Specify the intended transformation and data basis before estimating or applying parameters. Review missing-value handling and reference coding across the full dataset; one affine term or normalized vector does not establish comparable measurements or a fitted model.
References
Similar or alternative tools
- Reference Index Base Year Factor
Express a value relative to a supplied nonzero base value and index base.
- Scaled Missing Sentinel Collision Check
Check whether a supplied affine normalization collides with a missing sentinel.