ml_fpgrowth

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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 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()

Aliases
  • ml_fpgrowth
  • ml_association_rules
  • ml_freq_itemsets
Documentation reproduced from package sparklyr, version 1.0.4, License: Apache License 2.0 | file LICENSE

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