Streaming Multi-layer Ensemble Selection using Dynamic Genetic Algorithm

Anh Vu Luong, Tien Thanh Nguyen, Alan Wee-Chung Liew
2021 2021 Digital Image Computing: Techniques and Applications (DICTA)  
In this study, we introduce a novel framework for non-stationary data stream classification problems by modifying the Genetic Algorithm to search for the optimal configuration of a streaming multi-layer ensemble. We aim to connect the two sub-fields of non-stationary stream classification and evolutionary dynamic optimization. First, we present Streaming Multi-layer Ensemble (SMiLE) -a novel classification algorithm for non stationary data streams which comprises multiple layers of different
more » ... ssifiers. Second, we develop an ensemble selection method to obtain an optimal subset of classifiers for each layer of SMiLE. We formulate the selection process as a dynamic optimization problem and then solve it by adapting the Genetic Algorithm to the stream setting, generating a new classification framework called SMiLE_GA. Finally, we apply the proposed framework to address a real-world problem of insect stream classification, which relates to the automatic recognition of insects through optical sensors in real-time. The experiments showed that the proposed method achieves better prediction accuracy than several state-of-the-art benchmark algorithms for non-stationary data stream classification.
doi:10.1109/dicta52665.2021.9647220 fatcat:ejdkknrrzjbrlnpz35kwkjaqsi