Random Association Rule Threshold Exercise Generator

Description

Generate anchored synthetic baskets and a directed rule exercise with sampled thresholds, unrounded answers and explicitly rounded core evidence; association implies no causation.

Synthetic statistical data separates a specified generating model from the values observed in a finite draw. A model parameter, a sample summary, and the result of a fitted analysis answer different questions; retaining them separately makes numerical and statistical checks easier to interpret.

Generate anchored synthetic baskets and a directed rule exercise with sampled thresholds, unrounded answers and explicitly rounded core evidence; association implies no causation.

When to use this tool

Use this generator to create reproducible association rule threshold exercise cases from the supplied model or bank. Inspect the returned evidence before using cases in a test or exercise.

How to use the tool and how it works

Supply items, transactionCount, backgroundProbability, supportChoices, confidenceChoices, liftChoices in the field shapes below. Set seed when you need an explicit replay.
Run the tool and correct any input error. For generated controls, distinguish a successful fixture containing an invalid case from failure to generate the fixture.
Read transactions, rule, thresholds, answer. Use the conventions below. Keep answer-bearing fields separate when presenting an exercise.

Guarantee every item occurs in a singleton transaction, add sampled nonempty background baskets, and choose a directed item pair and thresholds. Calculate pair metrics, look up the mined rule, and test support, confidence, and lift inclusively.^[1]

Delegated operations used for this result: association rules. Their calculation or parsing conventions apply to the corresponding result fields.^[2]

Input field	Meaning and units	Accepted input
items	Items	Required. Array of Text; minimum UTF-16 length 1; maximum UTF-16 length 64.; minimum items 2; maximum items 6.
transactionCount	Transaction Count	Required. Safe integer; minimum 2; maximum 128.
backgroundProbability	Background Probability	Required. Finite number; minimum 0; maximum 1.
supportChoices	Support Choices	Required. Array of Finite number; maximum 1; strictly above 0.; minimum items 1; maximum items 8.
confidenceChoices	Confidence Choices	Required. Array of Finite number; minimum 0; maximum 1.; minimum items 1; maximum items 8.
liftChoices	Lift Choices	Required. Array of Finite number; minimum 0.; minimum items 1; maximum items 8.
seed	Optional numeric seed; takes precedence over context randomness. Without either, use the fixed tool.io default seed.	Optional. Safe integer.

Output field	Interpretation	Returned shape
transactions	Transactions	Required. Array of Array of Text; minimum UTF-16 length 1; maximum UTF-16 length 64.; minimum items 1; maximum items 6.; minimum items 2; maximum items 128.
rule	Rule	Required. Object; no unknown keys.
rule.antecedent	Antecedent	Required. Text; minimum UTF-16 length 1; maximum UTF-16 length 64.
rule.consequent	Consequent	Required. Text; minimum UTF-16 length 1; maximum UTF-16 length 64.
thresholds	Thresholds	Required. Object; no unknown keys.
thresholds.support	Support	Required. Finite number.
thresholds.confidence	Confidence	Required. Finite number.
thresholds.lift	Lift	Required. Finite number.
answer	Answer	Required. Object; no unknown keys.
answer.metrics	Metrics	Required. Object; no unknown keys.
answer.metrics.countA	Count A	Required. Safe integer; minimum 1; maximum 128.
answer.metrics.countB	Count B	Required. Safe integer; minimum 1; maximum 128.
answer.metrics.jointCount	Joint Count	Required. Safe integer; minimum 0; maximum 128.
answer.metrics.support	Support	Required. Finite number.
answer.metrics.confidence	Confidence	Required. Finite number.
answer.metrics.lift	Lift	Required. Finite number.
answer.coreRule	Core Rule	Required. Object; no unknown keys. or Null.
answer.meetsSupport	Meets Support	Required. Boolean.
answer.meetsConfidence	Meets Confidence	Required. Boolean.
answer.meetsLift	Meets Lift	Required. Boolean.
answer.accepted	Accepted	Required. Boolean.
randomness	Replay source and normalized 32-bit seed, or null seed for an advancing context source.	Required. Object; no unknown keys.
randomness.seed	Optional safe-integer replay seed; normalization and precedence are explained below.	Required. Safe integer. or Null.
randomness.source	Source	Required. Text; one of "context", "seed".

An explicit safe-integer seed takes precedence over injected context randomness and is normalized to an unsigned 32-bit integer. With no seed and no context source, replay uses the fixed tool.io default seed. A context source must return finite values from zero inclusive to one exclusive; its advancing state must be retained separately. randomness records the source and normalized seed, or null for context. These generators are not cryptographic random sources.

json

{
  "input": {
    "items": [
      "bread",
      "milk"
    ],
    "transactionCount": 4,
    "backgroundProbability": 0.5,
    "supportChoices": [
      0.25,
      0.5
    ],
    "confidenceChoices": [
      0.5,
      0.75
    ],
    "liftChoices": [
      1,
      1.5
    ],
    "seed": 42
  },
  "output": {
    "transactions": [
      [
        "bread"
      ],
      [
        "bread",
        "milk"
      ],
      [
        "bread",
        "milk"
      ],
      [
        "milk"
      ]
    ],
    "rule": {
      "antecedent": "milk",
      "consequent": "bread"
    },
    "thresholds": {
      "support": 0.25,
      "confidence": 0.75,
      "lift": 1.5
    },
    "answer": {
      "metrics": {
        "countA": 3,
        "countB": 3,
        "jointCount": 2,
        "support": 0.5,
        "confidence": 0.6666666666666666,
        "lift": 0.8888888888888888
      },
      "coreRule": {
        "antecedent": [
          "milk"
        ],
        "confidence": 0.666666666667,
        "consequent": [
          "bread"
        ],
        "lift": 0.888888888889,
        "support": 0.5
      },
      "meetsSupport": true,
      "meetsConfidence": false,
      "meetsLift": false,
      "accepted": false
    },
    "randomness": {
      "seed": 42,
      "source": "seed"
    }
  }
}

Limitations and assumptions

Support passes when jointCount reaches ceil(threshold times transaction count). A missing mined rule can coexist with explicit zero cooccurrence metrics. Threshold acceptance is synthetic evidence, not causation or business advice.
A replay requires the same complete input and implementation. The stated sampling convention applies within its eligible space. A finite draw does not exhaust all possible outputs; repeats remain possible unless a distinct-selection rule is explicit.
The field tables state structural bounds; cross-field constraints and bounded search or output budgets also apply. Unknown keys are rejected where the object contract disallows them. Input errors are distinct from null fields and deliberate invalid controls in a successful output.

Alternative or Complementary methods

For a supplied example, inspect the returned construction or delegated check directly. To evaluate a consumer, also test cases chosen for its own boundaries; a generated finite corpus does not establish exhaustive coverage.

References

Tool behavior and example: Random Association Rule Threshold Exercise Generator — tool.io
Calculation or validation: data-mining/association-rules — tool.io

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