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Tversky One Sided Penalty Parameter Tool

Calculate tversky one sided penalty parameter from explicit caller-supplied inputs.

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Description

Calculate Tversky score and alphaDerivative=-intersection*firstOnly/denominator² from denominator=intersection+alpha*firstOnly+beta*secondOnly.

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.

Calculate Tversky score and alphaDerivative=-intersection*firstOnly/denominator² from denominator=intersection+alpha*firstOnly+beta*secondOnly.

When to use this tool

Use Tversky One Sided Penalty Parameter 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 intersection, firstOnly, secondOnly, 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 score, alphaDerivative. Use the output convention below.

Calculate Tversky score and alphaDerivative=-intersection*firstOnly/denominator² from denominator=intersection+alpha*firstOnly+beta*secondOnly. Require nonnegative inputs and positive denominator.1

Input fieldMeaning and unitsAccepted input
intersectionIntersectionRequired. Finite number.
firstOnlyFirst OnlyRequired. Finite number.
secondOnlySecond OnlyRequired. Finite number.
alphaAlphaRequired. Finite number.
betaBetaRequired. Finite number.
Output fieldInterpretationReturned shape
scoreScoreRequired. Finite number.
alphaDerivativeAlpha DerivativeRequired. Finite number.
json
{
  "input": {
    "intersection": 3,
    "firstOnly": 2,
    "secondOnly": 1,
    "alpha": 0.5,
    "beta": 1
  },
  "output": {
    "score": 0.6,
    "alphaDerivative": -0.24
  }
}

Limitations and assumptions

  • The derivative holds other inputs fixed and is a continuous sensitivity term, not a discrete added-feature effect. No feature counts or penalty choices are inferred.
  • 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-one-sided-penalty-parameter — tool.io

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