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A parallel FP-growth algorithm to mine frequent itemsets. The algorithm is described in Li et al., PFP: Parallel FP-Growth for Query Recommendation. PFP distributes computation in such a way that each worker executes an independent group of mining tasks. The FP-Growth algorithm is described in Han et al., Mining frequent patterns without candidate generation.
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Model trained by FPGrowth, which holds frequent itemsets.
item type
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A parallel PrefixSpan algorithm to mine frequent sequential patterns. The PrefixSpan algorithm is described in J. Pei, et al., PrefixSpan: Mining Sequential Patterns Efficiently by Prefix-Projected Pattern Growth (http://doi.org/10.1109/ICDE.2001.914830).
Model fitted by PrefixSpan
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Generates association rules from a RDD[FreqItemset[Item]. This method only generates association rules which have a single item as the consequent.