This operator create frequent item sets from a given stream.
The result stream creates a tuple with 3 attributes:
- id: the number (a simple counter) of the pattern
- set: the frequent pattern, which is a list of tuples (a nested attribute ~ NF^2)
- support: the support of the pattern
- SUPPORT: The minimal support that defines what is frequent. This can be either a total number > 1.0 or a double between 0.0 and 1.0. The double indicates the percent in terms of the number of transactions.
- TRANSACTIONS: A Number of transactions that should be investigated
- A transaction is a snap-shot of a window. so each time when a window changes, there is a new transaction
- LEARNER: the algorithm that is used
- Currently implemented: fpgrowth, Weka (which in turn has further algorithms)
- ALGORITHM: A set of options to describe the algorithm
This example uses FP-Growth for finding frequent item sets. it does not need any parameters in algorithm