Use this method to discover frequent item combinations and implication-style association rules in transaction-like data under explicit support and confidence thresholds.

Transactions

Required object input.

Minimum support

Required number input.

Minimum confidence

Required number input.

Maximum itemset size

Required integer input.

Derive association rules and calculate support, confidence, and lift. The tool evaluates the supplied inputs together and returns the named outputs below; it does not infer omitted operating conditions or change the units shown.^[1]

Rules

The resulting rules returned as an object.

• Frequent co-occurrence does not imply causation or practical importance. Results are sensitive to basket definition, duplicate handling, rare items, threshold selection, sampling, and multiple comparisons; confidence can also be misleading when consequents are common.
• Use finite inputs in the displayed units and preserve more precision than the final presentation requires. Independently verify safety-critical, financial, compliance, or production decisions.

Review support, confidence, lift, leverage, and absolute counts together. Validate useful rules on held-out or later data and apply domain constraints before acting on them.

• Apriori Frequent Itemset Miner

  Find item combinations whose support meets a selected threshold.

• Oxygen Altitude Threshold

  Compare a flight altitude with a threshold supplied by the user and calculate feet above or below that threshold. Oxygen rules vary by jurisdiction, aircraft, duration, and crew/passenger status; this tool does not choose a legal threshold.

• English Pluralizer

  Apply common English plural spelling rules and a small irregular-noun table to a lowercase noun. English exceptions are extensive, so treat the result as a rule-based suggestion rather than a dictionary lookup.