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Similarity: Tversky Single Feature Contribution Tool

Return the numerator and denominator contribution of one binary feature to a Tversky score under supplied nonnegative asymmetry weights.

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Description

Return the numerator and denominator contribution of one binary feature to a Tversky score under supplied nonnegative asymmetry weights.

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 the numerator and denominator contribution of one binary feature to a Tversky score under supplied nonnegative asymmetry weights.

When to use this tool

Use Similarity: Tversky Single Feature Contribution 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 inLeft, inRight, alpha, beta. 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 result. Expand result to inspect the returned fields.

Return numeratorContribution one only when a feature is in both sets. Return denominatorContribution one for both, alpha for left-only, beta for right-only, or zero for neither, with nonnegative penalties, inside result.1

Input fieldMeaning and unitsAccepted input
inLeftIn LeftRequired. Boolean.
inRightIn RightRequired. Boolean.
alphaAlphaRequired. Finite number.
betaBetaRequired. Finite number.
Output fieldInterpretationReturned shape
resultResultRequired. Object.
json
{
  "input": {
    "inLeft": true,
    "inRight": false,
    "alpha": 0.3,
    "beta": 0.7
  },
  "output": {
    "result": {
      "numeratorContribution": 0,
      "denominatorContribution": 0.3
    }
  }
}

Limitations and assumptions

  • This is one feature's Tversky term, not the final ratio. Penalties and membership flags are supplied rather than chosen or verified from data.
  • Outputs are nested inside result. 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/tversky-single-feature-contribution — tool.io

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