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On Dynamic Feature Weighting for Feature Drifting Data Streams., , , , и . ECML/PKDD (2), том 9852 из Lecture Notes in Computer Science, стр. 129-144. Springer, (2016)Decision tree-based feature ranking in concept drifting data streams., , и . SAC, стр. 590-592. ACM, (2019)SFNClassifier: a scale-free social network method to handle concept drift., , и . SAC, стр. 786-791. ACM, (2014)Overcoming feature drifts via dynamic feature weighted k-nearest neighbor learning., , , , и . ICPR, стр. 2186-2191. IEEE, (2016)Classifier Pool Generation based on a Two-level Diversity Approach., , , , и . ICPR, стр. 2414-2421. IEEE, (2020)ADADRIFT: An Adaptive Learning Technique for Long-history Stream-based Recommender Systems., , и . SMC, стр. 2593-2600. IEEE, (2020)Univariate Time Series Prediction using Data Stream Mining Algorithms and Temporal Dependence., , и . ICAART (2), стр. 398-408. SCITEPRESS, (2022)Dynamically Selected Ensemble for Data Stream Classification., , , и . IJCNN, стр. 1-7. IEEE, (2021)SNCStream: a social network-based data stream clustering algorithm., , и . SAC, стр. 935-940. ACM, (2015)Learning regularized hoeffding trees from data streams., и . SAC, стр. 574-581. ACM, (2019)