Selected Ensemble of Classifiers for Handling Concept-drifting Data Streams
一种挖掘概念漂移数据流的选择性集成算法

In data streams concept is often not stable but change with time.We proposed a selective integration algorithm OSEN (Orientation based Selected ENsemble) for handling concept drift data streams.This algorithm selects a near optimal subset of base classifiers based on the output of each base classifier on validation dataset.Our experiments with synthetic data sets simulating abrupt (SEA) and gradual (Hyperplane) concept drifts demonstrate that selective integration of classifiers built over small time interv...