Available algorithms

Candidate generation based

TreeProjection based

FPGrowth

FPGrowth algorithm relies on two data structures, FPTree and HeaderTable. To know more about them and their, please refer to the documentation here data-structures.

FPGrowth algorithm relies on the following two routines.

ModalAssociationRules.patternbaseMethod
patternbase(item::Item, htable::HeaderTable, miner::Miner)::ConditionalPatternBase

Retrieve the ConditionalPatternBase of fptree based on item.

The conditional pattern based on a FPTree is the set of all the paths from the tree root to nodes containing item (not included). Each of these paths is represented by an EnhancedItemset.

The EnhancedItemsets in the returned ConditionalPatternBase are sorted decreasingly by gsupport.

See also Miner, ConditionalPatternBase, contributors, EnhancedItemset, fpgrowth, FPTree, Item, Itemset, WorldMask.

source

Also, FPGrowth requires the Miner to remember the Contributors associated with the extracted frequent itemsets. To add this functionality, we can define a new dispatch of initpowerups: it is automatically considered to enrich the miner, while building it together with fpgrowth as mining algorithm.