FPGrowth#
- class pyspark.mllib.fpm.FPGrowth[source]#
A Parallel FP-growth algorithm to mine frequent itemsets.
New in version 1.4.0.
Methods
train(data[, minSupport, numPartitions])Computes an FP-Growth model that contains frequent itemsets.
Methods Documentation
- classmethod train(data, minSupport=0.3, numPartitions=- 1)[source]#
Computes an FP-Growth model that contains frequent itemsets.
New in version 1.4.0.
- Parameters
- data
pyspark.RDD The input data set, each element contains a transaction.
- minSupportfloat, optional
The minimal support level. (default: 0.3)
- numPartitionsint, optional
The number of partitions used by parallel FP-growth. A value of -1 will use the same number as input data. (default: -1)
- data