FPGrowthModel

class pyspark.mllib.fpm.FPGrowthModel(java_model)

A FP-Growth model for mining frequent itemsets using the Parallel FP-Growth algorithm.

New in version 1.4.0.

Examples

>>> data = [["a", "b", "c"], ["a", "b", "d", "e"], ["a", "c", "e"], ["a", "c", "f"]]
>>> rdd = sc.parallelize(data, 2)
>>> model = FPGrowth.train(rdd, 0.6, 2)
>>> sorted(model.freqItemsets().collect())
[FreqItemset(items=['a'], freq=4), FreqItemset(items=['c'], freq=3), ...
>>> model_path = temp_path + "/fpm"
>>> model.save(sc, model_path)
>>> sameModel = FPGrowthModel.load(sc, model_path)
>>> sorted(model.freqItemsets().collect()) == sorted(sameModel.freqItemsets().collect())
True

Methods

call(name, *a)	Call method of java_model
freqItemsets()	Returns the frequent itemsets of this model.
load(sc, path)	Load a model from the given path.
save(sc, path)	Save this model to the given path.

Methods Documentation

call(name, *a)

Call method of java_model

freqItemsets()

Returns the frequent itemsets of this model.

New in version 1.4.0.

classmethod load(sc, path)

Load a model from the given path.

New in version 2.0.0.

save(sc, path)

Save this model to the given path.

New in version 1.3.0.