A Data Generator for Multi-Stream Data

We present a stream data generator. The generator is mainly intended for multiple interrelated streams, in particular for objects with temporal properties, which are fed by dependent streams. Such data are e.g. customers their transactions: learning a model of the customers requires considering the stream of their transactions. However, the generator can also be used for conventional stream data, e.g. for learning the concepts of the transaction stream only. The generator is appropriate for testing classification and clustering algorithms on concept discovery and adaptation to concept drift. The number of concepts in the data can be specified as parameter to the generator; the same holds for the membership of an instance to a class. Hence,it is also appropriate for synthetic datasets on overlapping classes or clusters.