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Pack logtalk -- logtalk-3.100.1/docs/handbook/_sources/libraries/fp_growth_pattern_miner.rst.txt

.. _library_fp_growth_pattern_miner:

fp_growth_pattern_miner

FP-growth frequent itemset miner for transaction datasets. The library depends on the frequent_pattern_mining_protocols support library, implements the generic pattern_miner_protocol defined in the pattern_mining_protocols core library, and mines frequent itemsets using recursive conditional pattern-base projection over a compact FP-tree whose nodes store parent links directly, plus header-table node chains derived from the final tree for direct conditional-base reconstruction, without candidate generation.

Requires a dataset implementing transaction_dataset_protocol with transactions represented as canonical sorted lists of unique declared items.

API documentation

Open the `../../apis/library_index.html#fp_growth_pattern_miner <../../apis/library_index.html#fp_growth_pattern_miner>`__ link in a web browser.

Loading

To load this library, load the loader.lgt file:

::

| ?- logtalk_load(fp_growth_pattern_miner(loader)).

Testing

To test this library predicates, load the tester.lgt file:

::

| ?- logtalk_load(fp_growth_pattern_miner(tester)).

Features

  • FP-tree Construction: Builds a compact prefix tree from frequent items ordered by global support.
  • Header and Parent Links: Stores parent links directly in tree nodes and derives header-table node chains from the final tree so conditional pattern bases are reconstructed by walking parent links instead of using a separate node index.
  • Pattern Growth: Mines frequent itemsets recursively from conditional pattern bases without candidate generation.
  • Canonical Transactions: Validates that transactions are sorted, duplicate-free, and restricted to declared items.
  • Flexible Support Thresholds: Supports relative minimum support and absolute minimum support count.
  • Model Export: Mined pattern collections can be exported as predicate clauses or written to a file.

Options

The mine/3 predicate accepts the following options:

  • minimum_support/1: Relative minimum support threshold in the interval ]0.0, 1.0]. The default is 0.5.
  • minimum_support_count/1: Absolute minimum support count. When both support options are provided, this option takes precedence.
  • maximum_pattern_length/1: Maximum itemset length to mine. The default is 1000, which is effectively capped by the longest transaction in the dataset.
  • minimum_pattern_length/1: Minimum itemset length retained in the mined result. The default is 1.

Pattern miner representation

The mined pattern miner result is represented by a compound term with the functor chosen by the implementation and arity 3. For example:

::

fp_growth_pattern_miner(ItemDomain, Patterns, Options)

Where:

  • ItemDomain: Canonical sorted list of declared dataset items.
  • Patterns: List of itemset(Items, SupportCount) terms ordered first by pattern length and then lexicographically.
  • Options: Effective mining options used to mine the frequent itemsets.

References

  1. Han, J., Pei, J., and Yin, Y. (2000) - "Mining frequent patterns without candidate generation".