UM

Browse/Search Results:  1-10 of 11 Help

Selected(0)Clear Items/Page:    Sort:
Accurate and efficient sequential ensemble learning for highly imbalanced multi-class data Journal article
Neural Networks, 2020,Volume: 128,Page: 268-278
Authors:  Vong,Chi Man;  Du,Jie
Favorite |  | TC[WOS]:0 TC[Scopus]:0 | Submit date:2021/03/11
Highly imbalanced data  Multi-class classification  Sequential ensemble learning  
Tackling class overlap and imbalance problems in software defect prediction Journal article
SOFTWARE QUALITY JOURNAL, 2018,Volume: 26,Issue: 1,Page: 97-125
Authors:  Chen, Lin;  Fang, Bin;  Shang, Zhaowei;  Tang, Yuanyan
Favorite |  | TC[WOS]:16 TC[Scopus]:25 | Submit date:2018/10/30
Software Defect Prediction  Class Imbalance  Class Overlap  Machine Learning  
A novel AdaBoost framework with robust threshold and structural optimization Journal article
IEEE Transactions on Cybernetics, 2018,Volume: 48,Issue: 1,Page: 64-76
Authors:  Zhang P.-B.;  Yang Z.-X.
Favorite |  | TC[WOS]:29 TC[Scopus]:29 | Submit date:2018/12/22
Adaboost Algorithm  Bounds Of Empirical Error  Ensemble Method  Generalization Error  Indoor Positioning System  Robust Threshold  Special Single-layer Neural Network  Structural Optimization  
ELM Meets RAE-ELM: A hybrid intelligent model for multiple fault diagnosis and remaining useful life predication of rotating machinery Conference paper
Proceedings of the International Joint Conference on Neural Networks, Vancouver, BC, Canada, 24-29 July 2016
Authors:  Yang Z.-X.;  Zhang P.-B.
Favorite |  | TC[WOS]:7 TC[Scopus]:10 | Submit date:2018/12/22
Extreme Learning Machine (Elm)  Fault Diagnosis  Hybrid Intelligent Model  Network  Predication  Remaining Useful Life  
GOBoost: G-mean optimized boosting framework for class imbalance learning Conference paper
Proceedings of the World Congress on Intelligent Control and Automation (WCICA), Guilin, China, 12-15 June 2016
Authors:  Yang Lu;  Yiu-ming Cheung;  Yuan Yan Tang
Favorite |  | TC[WOS]:3 TC[Scopus]:4 | Submit date:2019/02/11
Data-driven train operation models based on data mining and driving experience for the diesel-electric locomotive Journal article
Advanced Engineering Informatics, 2016,Volume: 30,Issue: 3,Page: 553-563
Authors:  Zhang C.-Y.;  Chen D.;  Yin J.;  Chen L.
Favorite |  | TC[WOS]:10 TC[Scopus]:11 | Submit date:2019/02/13
Automatic Train Operation  Data-driven Train Operation Model  Ensemble Learning  Machine Learning  Manual Driving  
A Robust AdaBoost.RT Based Ensemble Extreme Learning Machine Journal article
Mathematical Problems in Engineering, 2015,Volume: 2015
Authors:  Zhang P.;  Yang Z.
Favorite |  | TC[WOS]:18 TC[Scopus]:14 | Submit date:2018/12/22
Ensemble Extreme Learning Machine Based on a New Self-adaptive AdaBoost.RT Conference paper
Proceedings of ELM-2014, Singapore, December 8-10, 2014
Authors:  Pengbo Zhang;  Zhixin Yang
Favorite |  | TC[WOS]:0 TC[Scopus]:0 | Submit date:2019/04/02
Extreme Learning Machine  Single-hidden Layer Feedforward Networks  Self-adaptive Adaboost.rt Algorithm  Regression  Ensemble  
An Effective Method to Reduce False Alarms in Video Face Detection Conference paper
Applied Mechanics and Materials, Shijiazhuang, 2013
Authors:  Bing Li;  Yuanyan Tang;  Di Wen;  Zhenchao Zhang;  Boyang Ding
Favorite |  | TC[WOS]:0 TC[Scopus]:0 | Submit date:2019/02/11
False Alarms  Fusion Detector Structure  Haar-like Features  Hog Features  
ISABoost: A weak classifier inner structure adjusting based AdaBoost algorithm—ISABoost based application in scene categorization Journal article
Neurocomputing, 2013,Volume: 103,Page: 104-113
Authors:  Xueming Qian;  Yuan Yan Tang;  Zhe Yan;  Kaiyu Hang
Favorite |  | TC[WOS]:7 TC[Scopus]:8 | Submit date:2019/04/30
Adaboost  Scene Categorization  Pattern Classification  Back-propagation Networks  Svm  Weight Learning