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Non-stationary data sequence classification using online class priors estimationCHUNYU YANG; JIE ZHOU.Pattern recognition. 2008, Vol 41, Num 8, pp 2656-2664, issn 0031-3203, 9 p.Article

Mining Recurring Concepts in a Dynamic Feature SpaceGOMES, João Bártolo; MOHAMED MEDHAT GABER; SOUSA, Pedro A. C et al.IEEE transactions on neural networks and learning systems (Print). 2014, Vol 25, Num 1, pp 95-110, issn 2162-237X, 16 p.Article

A rank-one update method for least squares linear discriminant analysis with concept driftYEH, Yi-Ren; FRANK WANG, Yu-Chiang.Pattern recognition. 2013, Vol 46, Num 5, pp 1267-1276, issn 0031-3203, 10 p.Article

Data compression by volume prototypes for streaming dataTABATA, Kenji; SATO, Maiko; KUDO, Mineichi et al.Pattern recognition. 2010, Vol 43, Num 9, pp 3162-3176, issn 0031-3203, 15 p.Article

Predictive learning models for concept driftCASE, John; JAIN, Sanjay; KAUFMANN, Susanne et al.Theoretical computer science. 2001, Vol 268, Num 2, pp 323-349, issn 0304-3975Conference Paper

Exponentially weighted moving average charts for detecting concept driftROSS, Gordon J; ADAMS, Niall M; TASOULIS, Dimitris K et al.Pattern recognition letters. 2012, Vol 33, Num 2, pp 191-198, issn 0167-8655, 8 p.Article

Evolving fuzzy classifiers using different model architecturesANGELOV, P; LUGHOFER, E; ZHOU, X et al.Fuzzy sets and systems. 2008, Vol 159, Num 23, pp 3160-3182, issn 0165-0114, 23 p.Article

The Impact of Diversity on Online Ensemble Learning in the Presence of Concept DriftMINKU, Leandro L; WHITE, Allan P; XIN YAO et al.IEEE transactions on knowledge and data engineering. 2010, Vol 22, Num 5, pp 730-742, issn 1041-4347, 13 p.Article

Transfer estimation of evolving class priors in data stream classificationZHIHAO ZHANG; JIE ZHOU.Pattern recognition. 2010, Vol 43, Num 9, pp 3151-3161, issn 0031-3203, 11 p.Article

Random Set Framework for Context-Based Classification With Hyperspectral ImageryBOLTON, Jeremy; GADER, Paul.IEEE transactions on geoscience and remote sensing. 2009, Vol 47, Num 11, pp 3810-3821, issn 0196-2892, 12 p.Conference Paper

Ambiguous decision trees for mining concept-drifting data streamsJING LIU; XUE LI; WEICAI ZHONG et al.Pattern recognition letters. 2009, Vol 30, Num 15, pp 1347-1355, issn 0167-8655, 9 p.Article

An approach of support approximation to discover frequent patterns from concept-drifting data streams based on concept learningLI, Chao-Wei; JEA, Kuen-Fang.Knowledge and information systems (Print). 2014, Vol 40, Num 3, pp 639-671, issn 0219-1377, 33 p.Article

Ensemble of online neural networks for non-stationary and imbalanced data streamsGHAZIKHANI, Adel; MONSEFI, Reza; HADI SADOGHI YAZDI et al.Neurocomputing (Amsterdam). 2013, Vol 122, pp 535-544, issn 0925-2312, 10 p.Article

Online cost-sensitive neural network classifiers for non-stationary and imbalanced data streamsGHAZIKHANI, Adel; MONSEFI, Reza; HADI SADOGHI YAZDI et al.Neural computing & applications (Print). 2013, Vol 23, Num 5, pp 1283-1295, issn 0941-0643, 13 p.Article

Recurrent concepts in data streams classificationGAMA, Joao; KOSINA, Petr.Knowledge and information systems (Print). 2014, Vol 40, Num 3, pp 489-507, issn 0219-1377, 19 p.Article

Using instance-weighted naive Bayes for adapting concept drift in masquerade detectionSEN, Sevil.International journal of information security (Print). 2014, Vol 13, Num 6, pp 583-590, issn 1615-5262, 8 p.Article

Reacting to Different Types of Concept Drift: The Accuracy Updated Ensemble AlgorithmBRZEZINSKI, Dariusz; STEFANOWSKI, Jerzy.IEEE transactions on neural networks and learning systems (Print). 2014, Vol 25, Num 1, pp 81-94, issn 2162-237X, 14 p.Article

Dynamic classifier ensemble for positive unlabeled text stream classificationSHIRUI PAN; YANG ZHANG; XUE LI et al.Knowledge and information systems (Print). 2012, Vol 33, Num 2, pp 267-287, issn 0219-1377, 21 p.Article

Facing the reality of data stream classification: coping with scarcity of labeled dataMASUD, Mohammad M; WOOLAM, Clay; JING GAO et al.Knowledge and information systems (Print). 2012, Vol 33, Num 1, pp 213-244, issn 0219-1377, 32 p.Article

Early detection of gradual concept drifts by text categorization and Support Vector Machine techniques: The TRIO algorithmMARSEGUERRA, M.Reliability engineering & systems safety. 2014, Vol 129, pp 1-9, issn 0951-8320, 9 p.Article

Dealing With Concept Drifts in Process MiningJAGADEESH CHANDRA BOSE, R. P; VAN DER AALST, Wil M. P; ZLIOBAITE, Indrė et al.IEEE transactions on neural networks and learning systems (Print). 2014, Vol 25, Num 1, pp 154-171, issn 2162-237X, 18 p.Article

Dealing with temporal variation in patent categorizationD'HONDT, Eva; VERBERNE, Suzan; OOSTDIJK, Nelleke et al.Information retrieval (Boston). 2014, Vol 17, Num 5-6, pp 520-544, issn 1386-4564, 25 p.Article

Revisiting the effect of history on learning performance: the problem of the demanding lordGIANNAKOPOULOS, George; PALPANAS, Themis.Knowledge and information systems (Print). 2013, Vol 36, Num 3, pp 653-691, issn 0219-1377, 39 p.Article

A hybrid decision tree training method using data streamsWOZNIAK, Michal.Knowledge and information systems (Print). 2011, Vol 29, Num 2, pp 335-347, issn 0219-1377, 13 p.Article