Random Cooccurrence Lift Contrast Corpus Generator

Description

Construct and shuffle synthetic baskets from feasible count-controlled pair designs, returning contingency cells and delegated rule metrics without a causal interpretation.

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.

Construct and shuffle synthetic baskets from feasible count-controlled pair designs, returning contingency cells and delegated rule metrics without a causal interpretation.

When to use this tool

Use this generator to create reproducible cooccurrence lift contrast corpus 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 itemA, itemB, neitherItem, designs 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 cases. Use the conventions below. Keep answer-bearing fields separate when presenting an exercise.

Construct exact both, only-A, only-B, and neither transaction counts from each supplied design, using a separate neither-item label. Shuffle baskets and return pair metrics and mined itemset/rule evidence for comparison.^[1]

Input field	Meaning and units	Accepted input
itemA	Item A	Required. Text; minimum UTF-16 length 1; maximum UTF-16 length 64.
itemB	Item B	Required. Text; minimum UTF-16 length 1; maximum UTF-16 length 64.
neitherItem	Neither Item	Required. Text; minimum UTF-16 length 1; maximum UTF-16 length 64.
designs	Designs	Required. Array of Object; no unknown keys.; minimum items 2; maximum items 8.
designs[].label	Supplied display label.	Required. Text; minimum UTF-16 length 1; maximum UTF-16 length 64.
designs[].transactionCount	Transaction Count	Required. Safe integer; minimum 2; maximum 128.
designs[].countA	Count A	Required. Safe integer; minimum 1; maximum 128.
designs[].countB	Count B	Required. Safe integer; minimum 1; maximum 128.
designs[].jointCount	Joint Count	Required. Safe integer; minimum 0; maximum 128.
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
cases	Cases	Required. Array of Object; no unknown keys.; minimum items 2; maximum items 8.
cases[].label	Supplied display label.	Required. Text; minimum UTF-16 length 1; maximum UTF-16 length 64.
cases[].cells	Cells	Required. Object; no unknown keys.
cases[].cells.both	Both	Required. Safe integer; minimum 0; maximum 128.
cases[].cells.onlyA	Only A	Required. Safe integer; minimum 0; maximum 128.
cases[].cells.onlyB	Only B	Required. Safe integer; minimum 0; maximum 128.
cases[].cells.neither	Neither	Required. Safe integer; minimum 0; maximum 128.
cases[].transactions	Transactions	Required. Array of Array of Text; minimum UTF-16 length 1; maximum UTF-16 length 64.; minimum items 1; maximum items 2.; minimum items 2; maximum items 128.
cases[].metrics	Metrics	Required. Object; no unknown keys.
cases[].metrics.countA	Count A	Required. Safe integer; minimum 1; maximum 128.
cases[].metrics.countB	Count B	Required. Safe integer; minimum 1; maximum 128.
cases[].metrics.jointCount	Joint Count	Required. Safe integer; minimum 0; maximum 128.
cases[].metrics.support	Support	Required. Finite number.
cases[].metrics.confidence	Confidence	Required. Finite number.
cases[].metrics.lift	Lift	Required. Finite number.
cases[].mining	Mining	Required. Object; no unknown keys.
cases[].mining.itemsets	Itemsets	Required. Array of Object; no unknown keys.; minimum items 0; maximum items 41.
cases[].mining.itemsets[].items	Items	Required. Array of Text; minimum UTF-16 length 1; maximum UTF-16 length 64.; minimum items 1; maximum items 3.
cases[].mining.itemsets[].count	Count	Required. Safe integer; minimum 0; maximum 128.
cases[].mining.itemsets[].support	Support	Required. Finite number.
cases[].mining.itemsets[].coreSupport	Core Support	Required. Finite number.
cases[].mining.rules	Rules	Required. Array of Object; no unknown keys.; minimum items 0; maximum items 150.
cases[].mining.rules[].antecedent	Antecedent	Required. Array of Text; minimum UTF-16 length 1; maximum UTF-16 length 64.; minimum items 1; maximum items 3.
cases[].mining.rules[].consequent	Consequent	Required. Array of Text; minimum UTF-16 length 1; maximum UTF-16 length 64.; minimum items 1; maximum items 3.
cases[].mining.rules[].support	Support	Required. Finite number.
cases[].mining.rules[].confidence	Confidence	Required. Finite number.
cases[].mining.rules[].lift	Lift	Required. Finite number.
cases[].mining.rules[].coreSupport	Core Support	Required. Finite number.
cases[].mining.rules[].coreConfidence	Core Confidence	Required. Finite number.
cases[].mining.rules[].coreLift	Core Lift	Required. Finite number.
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": {
    "itemA": "A",
    "itemB": "B",
    "neitherItem": "other",
    "designs": [
      {
        "label": "rare-pair",
        "transactionCount": 4,
        "countA": 2,
        "countB": 2,
        "jointCount": 2
      },
      {
        "label": "common-pair",
        "transactionCount": 4,
        "countA": 2,
        "countB": 4,
        "jointCount": 2
      }
    ],
    "seed": 42
  },
  "output": {
    "cases": [
      {
        "label": "rare-pair",
        "cells": {
          "both": 2,
          "onlyA": 0,
          "onlyB": 0,
          "neither": 2
        },
        "transactions": [
          [
            "A",
            "B"
          ],
          [
            "other"
          ],
          [
            "A",
            "B"
          ],
          [
            "other"
          ]
        ],
        "metrics": {
          "countA": 2,
          "countB": 2,
          "jointCount": 2,
          "support": 0.5,
          "confidence": 1,
          "lift": 2
        },
        "mining": {
          "itemsets": [
            {
              "items": [
                "A"
              ],
              "count": 2,
              "support": 0.5,
              "coreSupport": 0.5
            },
            {
              "items": [
                "B"
              ],
              "count": 2,
              "support": 0.5,
              "coreSupport": 0.5
            },
            {
              "items": [
                "other"
              ],
              "count": 2,
              "support": 0.5,
              "coreSupport": 0.5
            },
            {
              "items": [
                "A",
                "B"
              ],
              "count": 2,
              "support": 0.5,
              "coreSupport": 0.5
            }
          ],
          "rules": [
            {
              "antecedent": [
                "A"
              ],
              "consequent": [
                "B"
              ],
              "support": 0.5,
              "confidence": 1,
              "lift": 2,
              "coreSupport": 0.5,
              "coreConfidence": 1,
              "coreLift": 2
            },
            {
              "antecedent": [
                "B"
              ],
              "consequent": [
                "A"
              ],
              "support": 0.5,
              "confidence": 1,
              "lift": 2,
              "coreSupport": 0.5,
              "coreConfidence": 1,
              "coreLift": 2
            }
          ]
        }
      },
      {
        "label": "common-pair",
        "cells": {
          "both": 2,
          "onlyA": 0,
          "onlyB": 2,
          "neither": 0
        },
        "transactions": [
          [
            "B"
          ],
          [
            "A",
            "B"
          ],
          [
            "A",
            "B"
          ],
          [
            "B"
          ]
        ],
        "metrics": {
          "countA": 2,
          "countB": 4,
          "jointCount": 2,
          "support": 0.5,
          "confidence": 1,
          "lift": 1
        },
        "mining": {
          "itemsets": [
            {
              "items": [
                "A"
              ],
              "count": 2,
              "support": 0.5,
              "coreSupport": 0.5
            },
            {
              "items": [
                "B"
              ],
              "count": 4,
              "support": 1,
              "coreSupport": 1
            },
            {
              "items": [
                "A",
                "B"
              ],
              "count": 2,
              "support": 0.5,
              "coreSupport": 0.5
            }
          ],
          "rules": [
            {
              "antecedent": [
                "A"
              ],
              "consequent": [
                "B"
              ],
              "support": 0.5,
              "confidence": 1,
              "lift": 1,
              "coreSupport": 0.5,
              "coreConfidence": 1,
              "coreLift": 1
            },
            {
              "antecedent": [
                "B"
              ],
              "consequent": [
                "A"
              ],
              "support": 0.5,
              "confidence": 0.5,
              "lift": 1,
              "coreSupport": 0.5,
              "coreConfidence": 0.5,
              "coreLift": 1
            }
          ]
        }
      }
    ],
    "randomness": {
      "seed": 42,
      "source": "seed"
    }
  }
}

Limitations and assumptions

Marginal and joint counts must be combinatorially feasible. Lift and confidence describe the planted finite distribution rather than causation or an observed market; the neither label is a real item in the generated baskets.
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 Cooccurrence Lift Contrast Corpus Generator — tool.io

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