Frequent Pattern Mining -- FPGrowth

A parallel FP-growth algorithm to mine frequent itemsets.

ml_fpgrowth(x, items_col = "items", min_confidence = 0.8,
  min_support = 0.3, prediction_col = "prediction",
  uid = random_string("fpgrowth_"), ...)

ml_association_rules(model)

ml_freq_itemsets(model)

Arguments

x

A spark_connection, ml_pipeline, or a tbl_spark.

items_col

Items column name. Default: "items"

min_confidence

Minimal confidence for generating Association Rule. min_confidence will not affect the mining for frequent itemsets, but will affect the association rules generation. Default: 0.8

min_support

Minimal support level of the frequent pattern. [0.0, 1.0]. Any pattern that appears more than (min_support * size-of-the-dataset) times will be output in the frequent itemsets. Default: 0.3

prediction_col

Prediction column name.

uid

A character string used to uniquely identify the ML estimator.

...

Optional arguments; currently unused.

model

A fitted FPGrowth model returned by ml_fpgrowth()