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)x |
A |
items_col |
Items column name. Default: "items" |
min_confidence |
Minimal confidence for generating Association Rule.
|
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 |
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