HRFuzzy: Holoentropy-enabled rough fuzzy classifier for evolving data streams
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[1] Hamid Reza Karimi,et al. New approach to delay-dependent H∞ control for continuous-time Markovian jump systems with time-varying delay and deficient transition descriptions , 2015, J. Frankl. Inst..
[2] Ernestina Menasalvas Ruiz,et al. Tracking recurrent concepts using context , 2012, Intell. Data Anal..
[3] Geoff Hulten,et al. Mining time-changing data streams , 2001, KDD '01.
[4] Derong Liu,et al. Detecting and Reacting to Changes in Sensing Units: The Active Classifier Case , 2014, IEEE Transactions on Systems, Man, and Cybernetics: Systems.
[5] Jerzy Stefanowski,et al. Reacting to Different Types of Concept Drift: The Accuracy Updated Ensemble Algorithm , 2014, IEEE Transactions on Neural Networks and Learning Systems.
[6] Hamid Reza Karimi,et al. model reduction for continuous-time Markovian jump systems with incomplete statistics of mode information , 2014, Int. J. Syst. Sci..
[7] Dimitris K. Tasoulis,et al. Nonparametric Monitoring of Data Streams for Changes in Location and Scale , 2011, Technometrics.
[8] Wei Fan,et al. Systematic data selection to mine concept-drifting data streams , 2004, KDD.
[9] Xiaodong Lin,et al. Active Learning From Stream Data Using Optimal Weight Classifier Ensemble , 2010, IEEE Transactions on Systems, Man, and Cybernetics, Part B (Cybernetics).
[10] Marcus A. Maloof,et al. Using additive expert ensembles to cope with concept drift , 2005, ICML.
[11] João Gama,et al. Tracking Recurring Concepts with Meta-learners , 2009, EPIA.
[12] Jianbin Qiu,et al. Approaches to T–S Fuzzy-Affine-Model-Based Reliable Output Feedback Control for Nonlinear Itô Stochastic Systems , 2017, IEEE Transactions on Fuzzy Systems.
[13] Philip S. Yu,et al. Mining concept-drifting data streams using ensemble classifiers , 2003, KDD '03.
[14] Jianbin Qiu,et al. Adaptive Fuzzy Backstepping Control for A Class of Nonlinear Systems With Sampled and Delayed Measurements , 2015, IEEE Transactions on Fuzzy Systems.
[15] Xindong Wu,et al. Mining in Anticipation for Concept Change: Proactive-Reactive Prediction in Data Streams , 2006, Data Mining and Knowledge Discovery.
[16] Jianbin Qiu,et al. Fuzzy-Model-Based Reliable Static Output Feedback $\mathscr{H}_{\infty }$ Control of Nonlinear Hyperbolic PDE Systems , 2016, IEEE Transactions on Fuzzy Systems.
[17] Jesús S. Aguilar-Ruiz,et al. A similarity-based approach for data stream classification , 2014, Expert Syst. Appl..
[18] Jiawei Han,et al. On Appropriate Assumptions to Mine Data Streams: Analysis and Practice , 2007, Seventh IEEE International Conference on Data Mining (ICDM 2007).
[19] Yong Zhang,et al. Weighted Fuzzy Observer-Based Fault Detection Approach for Discrete-Time Nonlinear Systems via Piecewise-Fuzzy Lyapunov Functions , 2016, IEEE Transactions on Fuzzy Systems.
[20] Jianbin Qiu,et al. A Combined Fault-Tolerant and Predictive Control for Network-Based Industrial Processes , 2016, IEEE Transactions on Industrial Electronics.
[21] Geoff Holmes,et al. New ensemble methods for evolving data streams , 2009, KDD.
[22] Hamid Reza Karimi,et al. A new design of H∞ filtering for continuous-time Markovian jump systems with time-varying delay and partially accessible mode information , 2013, Signal Process..
[23] Hamid Reza Karimi,et al. Filtering design for two-dimensional Markovian jump systems with state-delays and deficient mode information , 2014, Inf. Sci..
[24] Jerzy W. Grzymala-Busse,et al. Rough Sets , 1995, Commun. ACM.
[25] Jianbin Qiu,et al. Real-Time Fault Detection Approach for Nonlinear Systems and its Asynchronous T–S Fuzzy Observer-Based Implementation , 2017, IEEE Transactions on Cybernetics.
[26] Jianbin Qiu,et al. A Combined Adaptive Neural Network and Nonlinear Model Predictive Control for Multirate Networked Industrial Process Control , 2016, IEEE Transactions on Neural Networks and Learning Systems.
[27] Robert LIN,et al. NOTE ON FUZZY SETS , 2014 .
[28] Ernestina Menasalvas Ruiz,et al. Mining Recurring Concepts in a Dynamic Feature Space , 2014, IEEE Transactions on Neural Networks and Learning Systems.
[29] Sankar K. Pal,et al. Fuzzy models for pattern recognition : methods that search for structures in data , 1992 .
[30] J. MacQueen. Some methods for classification and analysis of multivariate observations , 1967 .
[31] Bhavani M. Thuraisingham,et al. Classification and Novel Class Detection in Concept-Drifting Data Streams under Time Constraints , 2011, IEEE Transactions on Knowledge and Data Engineering.
[32] David B. Skillicorn,et al. Classification Using Streaming Random Forests , 2011, IEEE Transactions on Knowledge and Data Engineering.
[33] Shengrui Wang,et al. Information-Theoretic Outlier Detection for Large-Scale Categorical Data , 2013, IEEE Transactions on Knowledge and Data Engineering.
[34] Grigorios Tsoumakas,et al. On the Utility of Incremental Feature Selection for the Classification of Textual Data Streams , 2005, Panhellenic Conference on Informatics.
[35] Li Guo,et al. E-Tree: An Efficient Indexing Structure for Ensemble Models on Data Streams , 2015, IEEE Transactions on Knowledge and Data Engineering.
[36] Piotr Duda,et al. Decision Trees for Mining Data Streams Based on the Gaussian Approximation , 2014, IEEE Transactions on Knowledge and Data Engineering.
[37] Charu C. Aggarwal,et al. Classification and Adaptive Novel Class Detection of Feature-Evolving Data Streams , 2013, IEEE Transactions on Knowledge and Data Engineering.