141 related articles for article (PubMed ID: 34435102)
1. Design of adaptive ensemble classifier for online sentiment analysis and opinion mining.
Kumar S; Singh R; Khan MZ; Noorwali A
PeerJ Comput Sci; 2021; 7():e660. PubMed ID: 34435102
[TBL] [Abstract][Full Text] [Related]
2. Adaptive Chunk-Based Dynamic Weighted Majority for Imbalanced Data Streams With Concept Drift.
Lu Y; Cheung YM; Yan Tang Y
IEEE Trans Neural Netw Learn Syst; 2020 Aug; 31(8):2764-2778. PubMed ID: 31825880
[TBL] [Abstract][Full Text] [Related]
3. Reacting to different types of concept drift: the Accuracy Updated Ensemble algorithm.
Brzezinski D; Stefanowski J
IEEE Trans Neural Netw Learn Syst; 2014 Jan; 25(1):81-94. PubMed ID: 24806646
[TBL] [Abstract][Full Text] [Related]
4. Selective ensemble-based online adaptive deep neural networks for streaming data with concept drift.
Guo H; Zhang S; Wang W
Neural Netw; 2021 Oct; 142():437-456. PubMed ID: 34273615
[TBL] [Abstract][Full Text] [Related]
5. Diverse Instance-Weighting Ensemble Based on Region Drift Disagreement for Concept Drift Adaptation.
Liu A; Lu J; Zhang G
IEEE Trans Neural Netw Learn Syst; 2021 Jan; 32(1):293-307. PubMed ID: 32217484
[TBL] [Abstract][Full Text] [Related]
6. Measuring the Effectiveness of Adaptive Random Forest for Handling Concept Drift in Big Data Streams.
AlQabbany AO; Azmi AM
Entropy (Basel); 2021 Jul; 23(7):. PubMed ID: 34356400
[TBL] [Abstract][Full Text] [Related]
7. An Adaptive Heterogeneous Online Learning Ensemble Classifier for Nonstationary Environments.
Museba T; Nelwamondo F; Ouahada K
Comput Intell Neurosci; 2021; 2021():6669706. PubMed ID: 33815495
[TBL] [Abstract][Full Text] [Related]
8. Application of Imbalanced Data Classification Quality Metrics as Weighting Methods of the Ensemble Data Stream Classification Algorithms.
Wegier W; Ksieniewicz P
Entropy (Basel); 2020 Jul; 22(8):. PubMed ID: 33286620
[TBL] [Abstract][Full Text] [Related]
9. Adversarial concept drift detection under poisoning attacks for robust data stream mining.
Korycki Ł; Krawczyk B
Mach Learn; 2022 Jun; ():1-36. PubMed ID: 35668720
[TBL] [Abstract][Full Text] [Related]
10. Adaptive Online Sequential ELM for Concept Drift Tackling.
Budiman A; Fanany MI; Basaruddin C
Comput Intell Neurosci; 2016; 2016():8091267. PubMed ID: 27594879
[TBL] [Abstract][Full Text] [Related]
11. Dynamic Ensemble Selection for Imbalanced Data Streams With Concept Drift.
Jiao B; Guo Y; Gong D; Chen Q
IEEE Trans Neural Netw Learn Syst; 2022 Jun; PP():. PubMed ID: 35731763
[TBL] [Abstract][Full Text] [Related]
12. Semantic relational machine learning model for sentiment analysis using cascade feature selection and heterogeneous classifier ensemble.
Yenkikar A; Babu CN; Hemanth DJ
PeerJ Comput Sci; 2022; 8():e1100. PubMed ID: 36262147
[TBL] [Abstract][Full Text] [Related]
13. Adaptive Semi-Supervised Classifier Ensemble for High Dimensional Data Classification.
Yu Z; Zhang Y; You J; Chen CLP; Wong HS; Han G; Zhang J
IEEE Trans Cybern; 2019 Feb; 49(2):366-379. PubMed ID: 29989979
[TBL] [Abstract][Full Text] [Related]
14. Fast adapting ensemble: a new algorithm for mining data streams with concept drift.
Ortíz Díaz A; del Campo-Ávila J; Ramos-Jiménez G; Frías Blanco I; Caballero Mota Y; Mustelier Hechavarría A; Morales-Bueno R
ScientificWorldJournal; 2015; 2015():235810. PubMed ID: 25879051
[TBL] [Abstract][Full Text] [Related]
15. Covariate shift estimation based adaptive ensemble learning for handling non-stationarity in motor imagery related EEG-based brain-computer interface.
Raza H; Rathee D; Zhou SM; Cecotti H; Prasad G
Neurocomputing (Amst); 2019 May; 343():154-166. PubMed ID: 32226230
[TBL] [Abstract][Full Text] [Related]
16. A novel bio-inspired hybrid multi-filter wrapper gene selection method with ensemble classifier for microarray data.
Nouri-Moghaddam B; Ghazanfari M; Fathian M
Neural Comput Appl; 2023; 35(16):11531-11561. PubMed ID: 34539088
[TBL] [Abstract][Full Text] [Related]
17. IWDA: Importance Weighting for Drift Adaptation in Streaming Supervised Learning Problems.
Fedeli F; Metelli AM; Trovo F; Restelli M
IEEE Trans Neural Netw Learn Syst; 2023 Oct; 34(10):6813-6823. PubMed ID: 37071516
[TBL] [Abstract][Full Text] [Related]
18. An Adaptive Deep Learning Framework for Dynamic Image Classification in the Internet of Things Environment.
Jameel SM; Hashmani MA; Rehman M; Budiman A
Sensors (Basel); 2020 Oct; 20(20):. PubMed ID: 33066579
[TBL] [Abstract][Full Text] [Related]
19. Driftage: a multi-agent system framework for concept drift detection.
Vieira DM; Fernandes C; Lucena C; Lifschitz S
Gigascience; 2021 Jun; 10(6):. PubMed ID: 34061207
[TBL] [Abstract][Full Text] [Related]
20. Combining multiple feature representations and AdaBoost ensemble learning for reducing false-positive detections in computer-aided detection of masses on mammograms.
Choi JY; Kim DH; Plataniotis KN; Ro YM
Annu Int Conf IEEE Eng Med Biol Soc; 2012; 2012():4394-7. PubMed ID: 23366901
[TBL] [Abstract][Full Text] [Related]
[Next] [New Search]
