Learning Imbalanced Datasets With Maximum Margin Loss

Mapping Intimacies ◽

10.1109/icip42928.2021.9506389 ◽

2021 ◽

Author(s):

Haeyong Kang ◽

Thang Vu ◽

Chang D. Yoo

Keyword(s):

Imbalanced Datasets ◽

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Faculty Opinions recommendation of The precision-recall plot is more informative than the ROC plot when evaluating binary classifiers on imbalanced datasets.

Faculty Opinions – Post-Publication Peer Review of the Biomedical Literature ◽

10.3410/f.725375858.793530299 ◽

2017 ◽

Author(s):

Michael Barnes ◽

David Watson

Keyword(s):

Imbalanced Datasets ◽

Binary Classifiers

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Contextual-distance Metric Based Laplacian Maximum Margin Criterion

ACTA AUTOMATICA SINICA ◽

10.3724/sp.j.1004.2010.01661 ◽

2011 ◽

Vol 36 (12) ◽

pp. 1661-1673

Author(s):

Jun GAO ◽

Shi-Tong WANG ◽

Xiao-Ming WANG

Keyword(s):

Distance Metric ◽

Maximum Margin ◽

Maximum Margin Criterion

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Uncorrelated Locality Preserving Projections Analysis Based on Maximum Margin Criterion

ACTA AUTOMATICA SINICA ◽

10.3724/sp.j.1004.2013.01575 ◽

2014 ◽

Vol 39 (9) ◽

pp. 1575-1580

Author(s):

Qu GONG ◽

Ping-Feng TANG

Keyword(s):

Locality Preserving Projections ◽

Maximum Margin ◽

Locality Preserving ◽

Maximum Margin Criterion

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Imbalanced datasets in the generation of fuzzy classification systems - an investigation using a multiobjective evolutionary algorithm based on decomposition

2016 IEEE International Conference on Fuzzy Systems (FUZZ-IEEE) ◽

10.1109/fuzz-ieee.2016.7737859 ◽

2016 ◽

Author(s):

Edward Hinojosa Cardenas ◽

Heloisa A. Camargo ◽

Yvan J. Tupac

Keyword(s):

Evolutionary Algorithm ◽

Classification Systems ◽

Fuzzy Classification ◽

Imbalanced Datasets ◽

Multiobjective Evolutionary Algorithm

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Feature Selection and Ensemble Learning Techniques in One-Class Classifiers: An Empirical Study of Two-Class Imbalanced Datasets

IEEE Access ◽

10.1109/access.2021.3051969 ◽

2021 ◽

Vol 9 ◽

pp. 13717-13726

Author(s):

Chih-Fong Tsai ◽

Wei-Chao Lin

Keyword(s):

Feature Selection ◽

Empirical Study ◽

Ensemble Learning ◽

Imbalanced Datasets ◽

Learning Techniques

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Supervised discriminant Isomap with maximum margin graph regularization for dimensionality reduction

Expert Systems with Applications ◽

10.1016/j.eswa.2021.115055 ◽

2021 ◽

pp. 115055

Author(s):

Hongchun Qu ◽

Lin Li ◽

Zhaoni Li ◽

Jian Zheng

Keyword(s):

Dimensionality Reduction ◽

Graph Regularization ◽

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Fast maximum margin matrix factorization for collaborative prediction

Proceedings of the 22nd international conference on Machine learning - ICML '05 ◽

10.1145/1102351.1102441 ◽

2005 ◽

Author(s):

Jasson D. M. Rennie ◽

Nathan Srebro

Keyword(s):

Matrix Factorization ◽

Maximum Margin ◽

Collaborative Prediction

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Adaptive Weighted Maximum Margin Criterion

2020 IEEE 3rd International Conference on Information Systems and Computer Aided Education (ICISCAE) ◽

10.1109/iciscae51034.2020.9236820 ◽

2020 ◽

Author(s):

Yuchen Fei ◽

Yan Wang

Keyword(s):

Maximum Margin ◽

Maximum Margin Criterion

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A Multi-Schematic Classifier-Independent Oversampling Approach for Imbalanced Datasets

IEEE Access ◽

10.1109/access.2021.3108450 ◽

2021 ◽

Vol 9 ◽

pp. 123358-123374

Author(s):

Saptarshi Bej ◽

Kristian Schulz ◽

Prashant Srivastava ◽

Markus Wolfien ◽

Olaf Wolkenhauer

Keyword(s):

Imbalanced Datasets

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Learning fuzzy classification rules from imbalanced datasets using multi-objective evolutionary algorithm

2015 Latin America Congress on Computational Intelligence (LA-CCI) ◽

10.1109/la-cci.2015.7435959 ◽

2015 ◽

Author(s):

C. Edward Hinojosa ◽

Heloisa A. Camargo ◽

V. Yvan J. Tupac

Keyword(s):

Evolutionary Algorithm ◽

Fuzzy Classification ◽

Classification Rules ◽

Imbalanced Datasets ◽

Multi Objective

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