Projects funded by the NCN


Information on the principal investigator and host institution

Information of the project and the call

Keywords

Equipment

Delete all

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

Information in the final report

  • Publication in academic press/journals (11)
  • Articles in post-conference publications (12)
  1. 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
  2. Dynamic Classifier Selection for Multi-Class Imbalanced Data
    Authors:
    Bartosz Krawczyk
    Academic press:
    Pattern Recognition (rok: 2020, tom: -, strony: -), Wydawca: Elsevier
    Status:
    Submitted
  3. 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
  4. 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
  5. 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
  6. 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
  7. 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
  8. 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
  9. 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
  10. 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
  11. 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
  1. 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
  2. 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
  3. 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
  4. 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
  5. 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
  6. 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
  7. 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
  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
  9. 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
  10. 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
  11. 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
  12. 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