An effective pattern-based Bayesian classifier for evolving data stream
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[1] Philip S. Yu,et al. Efficient algorithms for mining maximal high utility itemsets from data streams with different models , 2012, Expert Syst. Appl..
[2] Nir Friedman,et al. Bayesian Network Classifiers , 1997, Machine Learning.
[3] Jiawei Han,et al. Discriminative Frequent Pattern Analysis for Effective Classification , 2007, 2007 IEEE 23rd International Conference on Data Engineering.
[4] Geoff Hulten,et al. Mining time-changing data streams , 2001, KDD '01.
[5] Kotagiri Ramamohanarao,et al. Patterns Based Classifiers , 2007, World Wide Web.
[6] Geoffrey I. Webb,et al. Not So Naive Bayes: Aggregating One-Dependence Estimators , 2005, Machine Learning.
[7] Usama M. Fayyad,et al. Multi-Interval Discretization of Continuous-Valued Attributes for Classification Learning , 1993, IJCAI.
[8] José Francisco Martínez Trinidad,et al. A survey of emerging patterns for supervised classification , 2012, Artificial Intelligence Review.
[9] Philip S. Yu,et al. Mining concept-drifting data streams using ensemble classifiers , 2003, KDD '03.
[10] Mohammad Hadi Sadreddini,et al. A sliding window based algorithm for frequent closed itemset mining over data streams , 2013, J. Syst. Softw..
[11] Nick Cercone,et al. Max-FISM: Mining (recently) maximal frequent itemsets over data streams using the sliding window model , 2012, Comput. Math. Appl..
[12] Kotagiri Ramamohanarao,et al. A Bayesian Approach to Use Emerging Patterns for Classification , 2003, ADC.
[13] Dimitris Meretakis,et al. Extending naïve Bayes classifiers using long itemsets , 1999, KDD '99.
[14] Luca Cagliero,et al. EnBay: A Novel Pattern-Based Bayesian Classifier , 2013, IEEE Transactions on Knowledge and Data Engineering.
[15] Keun Ho Ryu,et al. Sliding window based weighted maximal frequent pattern mining over data streams , 2014, Expert Syst. Appl..
[16] Jean Paul Barddal,et al. A Survey on Ensemble Learning for Data Stream Classification , 2017, ACM Comput. Surv..
[17] Luca Cagliero,et al. RIB: A Robust Itemset-based Bayesian approach to classification , 2014, Knowl. Based Syst..
[18] Nan Jiang,et al. CFI-Stream: mining closed frequent itemsets in data streams , 2006, KDD '06.
[19] William Nick Street,et al. A streaming ensemble algorithm (SEA) for large-scale classification , 2001, KDD '01.
[20] Geoff Holmes,et al. MOA: Massive Online Analysis , 2010, J. Mach. Learn. Res..
[21] Zhihai Wang,et al. A lazy associative classifier for time series , 2015, Intell. Data Anal..
[22] Zhihai Wang,et al. Online Ensemble Using Adaptive Windowing for Data Streams with Concept Drift , 2016, Int. J. Distributed Sens. Networks.
[23] Wai Lam,et al. LEARNING BAYESIAN BELIEF NETWORKS: AN APPROACH BASED ON THE MDL PRINCIPLE , 1994, Comput. Intell..
[24] João Gama,et al. Learning Decision Rules from Data Streams , 2011, IJCAI.
[25] Suh-Yin Lee,et al. DSM-FI: an efficient algorithm for mining frequent itemsets in data streams , 2008, Knowledge and Information Systems.
[26] Andrew McCallum,et al. A comparison of event models for naive bayes text classification , 1998, AAAI 1998.
[27] Geoff Holmes,et al. Efficient data stream classification via probabilistic adaptive windows , 2013, SAC '13.
[28] Aijun An,et al. Mining top-k high utility patterns over data streams , 2014, Inf. Sci..
[29] Saso Dzeroski,et al. Learning model trees from evolving data streams , 2010, Data Mining and Knowledge Discovery.