Projects funded by the NCN

Information on the principal investigator and host institution

Information of the project and the call

Keywords

Equipment

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Classification methods of imbalance data for multi-class classsification task

2015/19/B/ST6/01597

Keywords:

classification imbalance data machine learning prepocessing

Descriptors:

  • ST6_11: Machine learning, statistical data processing and applications using signal processing (e.g. speech, image, video)

Panel:

ST6 - Computer science and informatics: informatics and information systems, computer science, scientific computing, intelligent systems

Host institution :

Politechnika Wrocławska, Wydział Elektroniki

woj. dolnośląskie

Other projects carried out by the institution 

Principal investigator (from the host institution):

prof. Michał Woźniak 

Number of co-investigators in the project: 4

Call: OPUS 10 - announced on 2015-09-15

Amount awarded: 440 044 PLN

Project start date (Y-m-d): 2016-07-22

Project end date (Y-m-d): 2020-01-21

Project duration:: 42 months (the same as in the proposal)

Project status: Project settled

Project description

Download the project description in a pdf file

Note - project descriptions were prepared by the authors of the applications themselves and placed in the system in an unchanged form.

Equipment purchased [PL]

  1. Stacja dokująca do stacji roboczej (504 PLN)
  2. stacja robocza (7 000 PLN)

Information in the final report

  • Publication in academic press/journals (11)
  • Articles in post-conference publications (12)
  1. Advanced Analysis of Data Streams for Critical Infrastructures Protection and Cybersecurity
    Authors:
    Barbara Bobowska, Michał Choraś, Michał Woźniak
    Academic press:
    Journal of Universal Computer Science (rok: 2018, tom: vol. 24, no. 5, strony: 622-633), Wydawca: J.UCS Consortium
    Status:
    Published
    DOI:
    brak - link to the publication
  2. Data stream classification using active learned neural networks
    Authors:
    Paweł Ksieniewicz, Michał Woźniak, Bogusław Cyganek, Andrzej A. Kasprzak, Krzysztof Walkowiak
    Academic press:
    Neurocomputing (rok: 2019, tom: vol. 353, strony: 74-82), Wydawca: Elsevier
    Status:
    Published
    DOI:
    10.1016/j.neucom.2018.05.130 - link to the publication
  3. Radial-Based Oversampling for Noisy Imbalanced Data Classification
    Authors:
    Michał Koziarski, Bartosz Krawczyk, Michał Woźniak
    Academic press:
    Neurocomputing (rok: 2019, tom: Volume 343, strony: 19-33), Wydawca: Elsevier
    Status:
    Published
    DOI:
    10.1016/j.neucom.2018.04.089 - link to the publication
  4. Local Ensemble Learning from Imbalanced and Noisy Data for Word Sense Disambiguation
    Authors:
    Bartosz Krawczyk, Bridget McInnes
    Academic press:
    Pattern Recognition (rok: 2018, tom: Volume 78, strony: 103-119), Wydawca: Elsevier
    Status:
    Accepted for publication
    DOI:
    10.028 - link to the publication
  5. CCR: Combined Cleaning and Resampling Algorithm for Imbalanced Data Classification
    Authors:
    Michał Koziarski, Michał Woźniak
    Academic press:
    International Journal of Applied Mathematics and Computer Science (rok: 2017, tom: 27(4), strony: 727-736), Wydawca: University of Zielona Góra
    Status:
    Published
    DOI:
    10.1515/amcs-2017-0050 - link to the publication
  6. Dynamic ensemble selection for multi-class classification with one-class classifiers
    Authors:
    Bartosz Krawczyk, Mikel Galar, Michał Woźniak, Humberto Bustince, Francisco Herrera
    Academic press:
    Pattern Recognition (rok: 2018, tom: Volume 83, strony: 34-51), Wydawca: Elsevier
    Status:
    Published
    DOI:
    10.1016/j.patcog.2018.05.015 - link to the publication
  7. Instance reduction for one-class classification
    Authors:
    Bartosz Krawczyk, Isaac Triguero, Salvador Garcia, Michał Woźniak, Francisco Herrera
    Academic press:
    Knowledge and Information Systems (rok: 2019, tom: 59, strony: 601–628), Wydawca: Springer
    Status:
    Published
    DOI:
    10.1007/s10115-018-1220-z - link to the publication
  8. Dynamic Classifier Selection for Multi-Class Imbalanced Data
    Authors:
    Bartosz Krawczyk
    Academic press:
    Pattern Recognition (rok: 2020, tom: -, strony: -), Wydawca: Elsevier
    Status:
    Submitted
    DOI:
    brak - link to the publication
  9. Radial-based oversampling for multiclass imbalanced data classification
    Authors:
    Bartosz Krawczyk, Michał Koziarski, Michał Woźniak
    Academic press:
    IEEE Transactions on Neural Networks and Learning Systems (rok: 2020, tom: 31(8), strony: 2818 - 2831), Wydawca: IEEE
    Status:
    Published
    DOI:
    10.1109/TNNLS.2019.2913673 - link to the publication
  10. Combined Cleaning and Resampling algorithm for multi-class imbalanced data with label noise
    Authors:
    Michał Koziarski, Michal Woźniak, Bartosz Krawczyk
    Academic press:
    Knowledge-Based Systems (rok: 2020, tom: vol. 204, strony: 106223), Wydawca: Elsevier
    Status:
    Published
    DOI:
    10.1016/j.knosys.2020.106223 - link to the publication
  11. The deterministic subspace method for constructing classifer ensembles
    Authors:
    Michał Koziarski, Bartosz Krawczyk, Michał Woźniak
    Academic press:
    Pattern Analysis and Applications (rok: 2017, tom: 20(4), strony: 981-990), Wydawca: Springer
    Status:
    Published
    DOI:
    10.1007/s10044-017-0655-2 - link to the publication
  1. Combining random subspace approach with smote oversampling for imbalanced data classification
    Authors:
    Paweł Ksieniewicz
    Conference:
    14th International Conference Hybrid Artificial Intelligent Systems HAIS 2019 (rok: 2019, ), Wydawca: Springer, LNCS vol. 11734
    Data:
    konferencja 4-6 września 2019
    Status:
    Published
  2. Experimental study on Modified Radial-Based Oversampling
    Authors:
    Barbara Bobowska, Michał Woźniak
    Conference:
    The 13th International Conference on Soft Computing Models in Industrial and Environmental Applications (rok: 2018, ), Wydawca: Springer series Advances in Intelligent Systems and Computing, vol 771
    Data:
    konferencja 6-8 czerwca 2018
    Status:
    Published
  3. Radial-based approach to imbalanced data oversampling
    Authors:
    Michał Koziarski, Bartosz Krawczyk, Michał Woźniak
    Conference:
    12th International Conference on Hybrid Artificial Intelligence Systems, HAIS 2017 (rok: 2017, ), Wydawca: Springer, LNCS vol. 10334
    Data:
    konferencja 21-23 czerwca
    Status:
    Published
    DOI:
    link to the publication
  4. Dealing with the task of imbalanced, multidimensional data classification using ensembles of exposers
    Authors:
    Paweł Ksieniewicz, Michał Woźniak
    Conference:
    First International Workshop on Learning with Imbalanced Domains: Theory and Applications w trakcie ECML-PKDD 2017 (rok: 2017, ), Wydawca: Proceedings of Machine Learning Research, vol. 74
    Data:
    konferencja 22 września 2017
    Status:
    Published
    DOI:
    link to the publication
  5. Multi-class Imbalance Data Oversampling for Vertebral Column Pathologies Classification
    Authors:
    Jose A. Saez, Hector Quintian, Bartosz Krawczyk, Michał Woźniak, Emilio Corchado
    Conference:
    13th International Conference on Hybrid Artificial Intelligence Systems, HAIS 2018 (rok: 2018, ), Wydawca: Springer
    Data:
    konferencja 20-22 czerwca 2018
    Status:
    Published
  6. Performance Analysis of Binarization Strategies for Multi-Class Imbalanced Data Classification
    Authors:
    Michał Żak, Michał Woźniak
    Conference:
    International Conference on Computational Science ICCS 2020 (rok: 2020, ), Wydawca: Springer LNCS vol. 12140
    Data:
    konferencja 3-5 czerwca 2020
    Status:
    Published
  7. Selecting local ensembles for multiclass imbalance data classification
    Authors:
    Bartosz Krawczyk, Alberto Cano, Michał Woźniak
    Conference:
    2018 International Joint Conference on Neural Networks (IJCNN) (rok: 2018, ), Wydawca: IEEE
    Data:
    konferencja 8-13 lipca 2018
    Status:
    Published
  8. Undersampled Majority Class Ensemble for highly imbalanced binary classification
    Authors:
    Paweł Ksieniewicz
    Conference:
    Second International Workshop on Learning with Imbalanced Domains: Theory and Applications (during ECML-PKDD 2018) (rok: 2019, ), Wydawca: Proceedings of Machine Learning Research, vol. 94
    Data:
    konferencja 10 września 2018
    Status:
    Published
    DOI:
    link to the publication
  9. Imbalance reduction techniques applied to ECG classification problem
    Authors:
    Jędrzej Kozal, Paweł Ksieniewicz
    Conference:
    20th International Conference on Intelligent Data Engineering and Automated Learning - IDEAL 2019 (rok: 2019, ), Wydawca: Springer, LNCS vol. 11872
    Data:
    konferencja 14-16 listopada 2019
    Status:
    Published
  10. Imbalanced Data Classification Based on Feature Selection Techniques
    Authors:
    Paweł Ksienieiwicz, Michał Woźniak
    Conference:
    International Conference on Intelligent Data Engineering and Automated Learning – IDEAL 2018 (rok: 2018, ), Wydawca: Springer, Lecture Notes in Computer Science book series (LNCS, volume 11315)
    Data:
    konferencja 21-23 listopada 2018
    Status:
    Published
  11. Leveraging Ensemble Pruning for Imbalanced Data Classification
    Authors:
    Bartosz Krawczyk, Michał Woźniak
    Conference:
    2018 IEEE International Conference on Systems, Man, and Cybernetics (SMC) (rok: 2018, ), Wydawca: IEEE
    Data:
    konferencja 7-10 października 2018
    Status:
    Published
  12. SMOTE algorithm variations in balancing data streams
    Authors:
    Bogdan Gulowaty, Paweł Ksieniewicz
    Conference:
    20th International Conference on Intelligent Data Engineering and Automated Learning - IDEAL 2019 (rok: 2019, ), Wydawca: Springer, LNCS vol. 11872
    Data:
    konferencja 14-16 listopada 2019
    Status:
    Published

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