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Weighted Overlap One Weight Sensitivity Tool

Calculate weighted overlap one weight sensitivity from explicit caller-supplied inputs.

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Description

Return derivative=((inIntersection?referenceWeight:0)-(inReference?intersectionWeight:0))/referenceWeight².

A similarity term depends on the comparison universe, missing-value policy, treatment of repeated features, and normalization. A score can also have a caller-selected value when its mathematical denominator vanishes. Those conventions matter before interpreting a threshold or comparing methods.

Return derivative=((inIntersection?referenceWeight:0)-(inReference?intersectionWeight:0))/referenceWeight².

When to use this tool

Use Weighted Overlap One Weight Sensitivity when you need this particular comparison term, normalization, domain condition, or empty-result policy in a larger matching workflow.

How to use the tool and how it works

  1. Enter intersectionWeight, referenceWeight, inIntersection, inReference. Use the units and conventions below.
  2. Run the tool. Correct any format, range, or cross-field input error before interpreting the output.
  3. Read derivative. Use the output convention below.

Return derivative=((inIntersection?referenceWeight:0)-(inReference?intersectionWeight:0))/referenceWeight². Require nonnegative intersection weight within positive reference weight and intersection membership implying reference membership.1

Input fieldMeaning and unitsAccepted input
intersectionWeightIntersection WeightRequired. Finite number.
referenceWeightReference WeightRequired. Finite number.
inIntersectionIn IntersectionRequired. Boolean.
inReferenceIn ReferenceRequired. Boolean.
Output fieldInterpretationReturned shape
derivativeDerivativeRequired. Finite number.
json
{
  "input": {
    "intersectionWeight": 3,
    "referenceWeight": 5,
    "inIntersection": true,
    "inReference": true
  },
  "output": {
    "derivative": 0.08
  }
}

Limitations and assumptions

  • This is a local derivative of intersection/reference weight under one feature perturbation. It does not construct weights, choose an overlap metric, or estimate uncertainty.
  • The field tables state structural bounds; the mechanics also specify cross-field constraints. Malformed inputs and unsupported domains cause errors. A successful false flag, empty branch value, or zero placeholder has the meaning stated above and is distinct from an input error.
  • 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. Signed zero is exported as zero.

Alternative or Complementary methods

Compare methods only after aligning feature definitions, missingness, empty policies, multiplicities, and normalizers. Use a complete comparison when the tool returns only one contribution or count check.

References

  1. Calculation and input contract: similarity/weighted-overlap-one-weight-sensitivity — tool.io

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