ml_fpgrowth
From sparklyr v0.8.2
by Javier Luraschi
Frequent Pattern Mining -- FPGrowth
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
- x
A
spark_connection,ml_pipeline, or atbl_spark.- items_col
Items column name. Default: "items"
- min_confidence
Minimal confidence for generating Association Rule.
min_confidencewill 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()
Community examples
Looks like there are no examples yet.