SCBA: An evolving rules-based model for stream data classification

Recently, mining data streams for actionable insights has become an important and challenging task for a wide range of applications in finance, World Wide Web, scientific researches, etc. A rule-based model named SCBA (stream classification based on association rules) was developed for stream data classification based on the evolving rule base. SCBA dynamically selects class association rules from the rule base to update a single classifier to catch the concept drifts in stream data. Compared with the well-known algorithms as decision tree and ensemble classifiers, SCBA has the merits of faster adapting to concept drifts and faster responding to applications.