Pawel Ksieniewicz

Opt. Switch. Netw., 2022

Statistical Drift Detection Ensemble for batch processing of data streams.

[BibT_eX]

[DOI]

Knowl. Based Syst., 2022

Stream-learn - open-source Python library for difficult data stream batch analysis.

[BibT_eX]

[DOI]

Neurocomputing, 2022

problexity - an open-source Python library for binary classification problem complexity assessment.

[BibT_eX]

[DOI]

CoRR, 2022

Lifelong Learning Natural Language Processing Approach for Multilingual Data Classification.

[BibT_eX]

[DOI]

CoRR, 2022

Hybrid Regression Model for Link Dimensioning in Spectrally-Spatially Flexible Optical Networks.

[BibT_eX]

[DOI]

IEEE Access, 2022

Data complexity and classification accuracy correlation in oversampling algorithms.

[BibT_eX]

[DOI]

Proceedings of the Fourth International Workshop on Learning with Imbalanced Domains: Theory and Applications, 2022

Imbalanced Data Stream Classification Assisted by Prior Probability Estimation.

[BibT_eX]

[DOI]

Proceedings of the International Joint Conference on Neural Networks, 2022

Inductive Parallel Learning for Multiple Classification Problems.

[BibT_eX]

[DOI]

Weronika Borek

Proceedings of the International Joint Conference on Neural Networks, 2022

Data stream generation through real concept's interpolation.

[BibT_eX]

[DOI]

Proceedings of the 30th European Symposium on Artificial Neural Networks, 2022

Feature Integration Strategies for Multilingual Fake News Classification.

[BibT_eX]

[DOI]

Proceedings of the IEEE International Conference on Big Data, 2022

2021

Fusion of linear base classifiers in geometric space.

[BibT_eX]

[DOI]

Robert Burduk

Knowl. Based Syst., 2021

The prior probability in the batch classification of imbalanced data streams.

[BibT_eX]

[DOI]

Konstantinos P. Demestichas

Neurocomputing, 2021

How to design the fair experimental classifier evaluation.

[BibT_eX]

[DOI]

Appl. Soft Comput., 2021

Advanced Machine Learning techniques for fake news (online disinformation) detection: A systematic mapping study.

[BibT_eX]

[DOI]

Michal Choras

Agata Gielczyk

Álvaro Herrero

Konstantina Remoundou

Daniel Urda

Appl. Soft Comput., 2021

Prior Probability Estimation in Dynamically Imbalanced Data Streams.

[BibT_eX]

[DOI]

Proceedings of the International Joint Conference on Neural Networks, 2021

Analysis of Variance Application in the Construction of Classifier Ensemble Based on Optimal Feature Subset for the Task of Supporting Glaucoma Diagnosis.

[BibT_eX]

[DOI]

Dominika Sulot

Proceedings of the Computational Science - ICCS 2021, 2021

2020

Application of Imbalanced Data Classification Quality Metrics as Weighting Methods of the Ensemble Data Stream Classification Algorithms.

[BibT_eX]

[DOI]

Weronika Wegier

Entropy, 2020

stream-learn - open-source Python library for difficult data stream batch analysis.

[BibT_eX]

[DOI]

CoRR, 2020

Fake News Detection from Data Streams.

[BibT_eX]

[DOI]

Proceedings of the 2020 International Joint Conference on Neural Networks, 2020

Sentiment Analysis for Fake News Detection by Means of Neural Networks.

[BibT_eX]

[DOI]

Proceedings of the Computational Science - ICCS 2020, 2020

Pattern Recognition Model to Aid the Optimization of Dynamic Spectrally-Spatially Flexible Optical Networks.

[BibT_eX]

[DOI]

Proceedings of the Computational Science - ICCS 2020, 2020

Clustering and Weighted Scoring in Geometric Space Support Vector Machine Ensemble for Highly Imbalanced Data Classification.

[BibT_eX]

[DOI]

Robert Burduk

Proceedings of the Computational Science - ICCS 2020, 2020

Standard Decision Boundary in a Support-Domain of Fuzzy Classifier Prediction for the Task of Imbalanced Data Classification.

[BibT_eX]

[DOI]

Proceedings of the Computational Science - ICCS 2020, 2020

Combination of Active and Random Labeling Strategy in the Non-stationary Data Stream Classification.

[BibT_eX]

[DOI]

Proceedings of the Artificial Intelligence and Soft Computing, 2020

2019

Data stream classification using active learned neural networks.

[BibT_eX]

[DOI]

Neurocomputing, 2019

Machine Learning Methods for Fake News Classification.

[BibT_eX]

[DOI]

Proceedings of the Intelligent Data Engineering and Automated Learning - IDEAL 2019, 2019

Imbalance Reduction Techniques Applied to ECG Classification Problem.

[BibT_eX]

[DOI]

Jedrzej Kozal

Proceedings of the Intelligent Data Engineering and Automated Learning - IDEAL 2019, 2019

A Genetic-Based Ensemble Learning Applied to Imbalanced Data Classification.

[BibT_eX]

[DOI]

Jakub Klikowski

Proceedings of the Intelligent Data Engineering and Automated Learning - IDEAL 2019, 2019

SMOTE Algorithm Variations in Balancing Data Streams.

[BibT_eX]

[DOI]

Bogdan Gulowaty

Proceedings of the Intelligent Data Engineering and Automated Learning - IDEAL 2019, 2019

Classifier Selection for Highly Imbalanced Data Streams with Minority Driven Ensemble.

[BibT_eX]

[DOI]

Proceedings of the Artificial Intelligence and Soft Computing, 2019

Combining Random Subspace Approach with smote Oversampling for Imbalanced Data Classification.

[BibT_eX]

[DOI]

Proceedings of the Hybrid Artificial Intelligent Systems - 14th International Conference, 2019

2018

Ensemble of Extreme Learning Machines with trained classifier combination and statistical features for hyperspectral data.

[BibT_eX]

[DOI]

Neurocomputing, 2018

Undersampled Majority Class Ensemble for highly imbalanced binary classification.

[BibT_eX]

[DOI]

Proceedings of the Second International Workshop on Learning with Imbalanced Domains: Theory and Applications, 2018

Imbalanced Data Classification Based on Feature Selection Techniques.

[BibT_eX]

[DOI]

Proceedings of the Intelligent Data Engineering and Automated Learning - IDEAL 2018, 2018

Combined Classifier Based on Quantized Subspace Class Distribution.

[BibT_eX]

[DOI]

Proceedings of the Intelligent Data Engineering and Automated Learning - IDEAL 2018, 2018

An Empirical Insight Into Concept Drift Detectors Ensemble Strategies.

[BibT_eX]

[DOI]

Proceedings of the 2018 IEEE Congress on Evolutionary Computation, 2018

2017

Paired feature multilayer ensemble - concept and evaluation of a classifier.

[BibT_eX]

[DOI]

Manuel Graña

J. Intell. Fuzzy Syst., 2017

Dealing with the task of imbalanced, multidimensional data classification using ensembles of exposers.

[BibT_eX]

[DOI]

Proceedings of the First International Workshop on Learning with Imbalanced Domains: Theory and Applications, 2017

2016

A First Attempt to Construct Effective Concept Drift Detector Ensembles.

[BibT_eX]

[DOI]

Proceedings of the Image Processing and Communications Challenges 8, 2016

Active Learning Classification of Drifted Streaming Data.

[BibT_eX]

[DOI]

Proceedings of the International Conference on Computational Science 2016, 2016

Active Learning Classifier for Streaming Data.

[BibT_eX]

[DOI]

Proceedings of the Hybrid Artificial Intelligent Systems - 11th International Conference, 2016

Ensemble of One-Dimensional Classifiers for Hyperspectral Image Analysis.

[BibT_eX]

[DOI]

Proceedings of the Data Mining and Big Data, First International Conference, 2016

Ensembles of Heterogeneous Concept Drift Detectors - Experimental Study.

[BibT_eX]

[DOI]

Proceedings of the Computer Information Systems and Industrial Management, 2016

2015

A novel hyperspectral segmentation algorithm - concept and evaluation.

[BibT_eX]

[DOI]

Log. J. IGPL, 2015

Blurred Labeling Segmentation Algorithm for Hyperspectral Images.

[BibT_eX]

[DOI]

Manuel Graña

Proceedings of the Computational Collective Intelligence - 7th International Conference, 2015

Artificial Photoreceptors for Ensemble Classification of Hyperspectral Images.

[BibT_eX]

[DOI]

Proceedings of the 9th International Conference on Computer Recognition Systems CORES 2015, 2015

2014

Hyperspectral Image Analysis Based on Quad Tree Decomposition.

[BibT_eX]

[DOI]

Proceedings of the International Joint Conference SOCO'14-CISIS'14-ICEUTE'14, 2014

Hyperspectral Image Analysis Based on Color Channels and Ensemble Classifier.

[BibT_eX]

[DOI]