Frequent Pattern Mining – FPGrowth

R/ml_fpm_fpgrowth.R

ml_fpgrowth

Description

A parallel FP-growth algorithm to mine frequent itemsets.

Usage

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

Arguments	Description
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()