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

.. _library_spade_pattern_miner:

spade_pattern_miner

SPADE sequential pattern miner for sequence datasets. The library depends on the sequential_pattern_mining_protocols support library, implements the generic pattern_miner_protocol defined in the pattern_mining_protocols core library, and mines frequent sequential patterns using Zaki's equivalence-class decomposition with temporal joins over vertical occurrence lists keyed by sequence and event identifiers.

Requires a dataset implementing sequence_dataset_protocol with sequences represented as ordered lists of canonical sorted itemsets over a declared item domain.

API documentation

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

Loading

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

::

| ?- logtalk_load(spade_pattern_miner(loader)).

Testing

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

::

| ?- logtalk_load(spade_pattern_miner(tester)).

Features

  • Equivalence-Class Decomposition: Mines frequent sequences using Zaki's equivalence-class decomposition over prefix-sharing classes.
  • Vertical Occurrence Lists: Represents frequent patterns using sequence and event occurrence lists.
  • Active Class Candidate Pruning: Restricts class joins to members that occur in the supporting sequences of the current prefix, using per-sequence member-id indexes instead of storing full pattern terms in the sequence index.
  • Same-Event and Sequence Extensions: Supports both itemset growth and next-event sequence growth.
  • Canonical Sequences: Validates that itemsets are sorted, duplicate-free, non-empty, 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 total number of items in a mined sequential pattern. The default is 1000, effectively capped by the longest sequence in the dataset.
  • minimum_pattern_length/1: Minimum total number of items 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:

::

spade_pattern_miner(ItemDomain, Patterns, Options)

Where:

  • ItemDomain: Canonical sorted list of declared dataset items.
  • Patterns: List of sequence_pattern(Pattern, SupportCount) terms ordered first by total item count and then lexicographically.
  • Options: Effective mining options used to mine the frequent sequential patterns.

References

  1. Zaki, M. J. (2001) - "SPADE: An efficient algorithm for mining frequent sequences".