The KnowledgeFlow interface is a powerful new addition to Weka. At this moment, this new interface is not yet complete and not well documented. Nevertheless, it offers a compelling alternative to the other Weka graphical interfaces and some capabilities not available in the Explorer and Experimenter interface.

The idea behind the KnowledgeFlow interface is the “data-flow” and is similar to the one available in SAS. The user is presented with a layout canvas where they will place components. These components are then connected together to form a “knowledge flow” that will determine how the data will be processed, analyzed and reported. All of Weka’s clustering and Classification algorithms including some extra tools are available in KnowledgeFlow.

A major advantage of the KnowledgeFlow interface is that it can handle data either incrementally or in batches while the Explorer can only handle data in batches. This is of practical importance when handling extremely large and/or unlimited data. For this to be useful, Weka also provides classifiers that can handle data incrementally and be updated on an instance by instance basis. We will be examining the KnowledgeFlow in more detail later.