Investigating the influence of the choice of the ensemble members in accuracy and diversity of selection-based and fusion-based methods for ensembles-Reference-Cited by-同舟云学术

Investigating the influence of the choice of the ensemble members in accuracy and diversity of selection-based and fusion-based methods for ensembles

Published:2007-03 Issue:4 Volume:28 Page:472-486
ISSN:0167-8655
Container-title:Pattern Recognition Letters
language:en
Short-container-title:Pattern Recognition Letters

Author:

Canuto Anne M.P.,Abreu Marjory C.C.,de Melo Oliveira Lucas,Xavier João C.,Santos Araken de M.

Publisher

Elsevier BV

Subject

Artificial Intelligence,Computer Vision and Pattern Recognition,Signal Processing,Software

Reference27 articles.

1. Ensemble diversity measures and their application to thinning;Banfield;Information Fusion,2005

2. Blake, C.L., Merz, C.J., 1998. UCI Repository of machine learning databases. University of California, Department of Information and Computer Science, Irvine, CA. .

3. Bagging predictors;Breiman;Machine Learning,1996

4. Breiman, L., 1999. Using adaptive bagging to Debias regressions, Technical report 547, Dept. Statistics, University of California, Berkeley.

5. Canuto, A., 2001. Combining neural networks and fuzzy logic for applications in character recognition. Ph.D. thesis, University of Kent.

Cited by 67 articles. 订阅此论文施引文献订阅此论文施引文献，注册后可以免费订阅5篇论文的施引文献，订阅后可以查看论文全部施引文献

1. A Hybrid Model for Abnormalities Detection in Upper Extremity Radiographs;2024 IEEE International Conference on Information Technology, Electronics and Intelligent Communication Systems (ICITEICS);2024-06-28

2. The Dynamic Selection of Combination Methods in Classifier Ensembles by Region of Competence;Artificial Neural Networks and Machine Learning – ICANN 2023;2023

3. DNEF: A New Ensemble Framework Based on Deep Network Structure;Computers, Materials & Continua;2023

4. Non-Contact Supervision of COVID-19 Breathing Behaviour With FMCW Radar and Stacked Ensemble Learning Model in Real-Time;IEEE Transactions on Biomedical Circuits and Systems;2022-08

5. Empirical Analysis of Ensemble Learning for Imbalanced Credit Scoring Datasets: A Systematic Review;Wireless Communications and Mobile Computing;2022-06-15