In this paper, we present new approaches to handling drift and shift in on-line data streams with the help of evolving fuzzy systems (EFS), which are characterized by the fact tha...
As data streams are gaining prominence in a growing number of emerging application domains, classification on data streams is becoming an active research area. Currently, the typi...
A Genetic Programming based boosting ensemble method for the classification of distributed streaming data is proposed. The approach handles flows of data coming from multiple loc...
Gianluigi Folino, Clara Pizzuti, Giandomenico Spez...
We present a new approach for dealing with distribution change and concept drift when learning from data sequences that may vary with time. We use sliding windows whose size, inst...
Abstract--A new approach to the online classification of streaming data is introduced in this paper. It is based on a selfdeveloping (evolving) fuzzy-rule-based (FRB) classifier sy...