Bartosz Krawczyk

发表

A survey on data preprocessing for data stream mining: Current status and future directions

Francisco Herrera, Sergio Ramírez-Gallego, Bartosz Krawczyk, 2017, Neurocomputing.

Clustering-based ensembles for one-class classification

Bartosz Krawczyk, Michal Wozniak, Boguslaw Cyganek, 2014, Inf. Sci..

Classifier Committee Based on Feature Selection Method for Obstructive Nephropathy Diagnosis

Bartosz Krawczyk, B. Krawczyk, 2011 .

Combining one-class classifiers for imbalanced classification of breast thermogram features

Gerald Schaefer, Bartosz Krawczyk, Michal Wozniak, 2013, 2013 Fourth International Workshop on Computational Intelligence in Medical Imaging (CIMI).

Learning from imbalanced data: open challenges and future directions

Bartosz Krawczyk, B. Krawczyk, 2016, Progress in Artificial Intelligence.

Neural Network Ensemble Based on Feature Selection for Non-Invasive Recognition of Liver Fibrosis Stage

Bartosz Krawczyk, Tomasz Orczyk, Michał Woźniak, 2014 .

Towards Highly Accurate Coral Texture Images Classification Using Deep Convolutional Neural Networks and Data Augmentation pdf

Francisco Herrera, Bartosz Krawczyk, Siham Tabik, 2018, Expert Syst. Appl..

A first attempt on evolutionary prototype reduction for nearest neighbor one-class classification

Francisco Herrera, Salvador García, Bartosz Krawczyk, 2014, 2014 IEEE Congress on Evolutionary Computation (CEC).

Weighted one-class classification for different types of minority class examples in imbalanced data

Francisco Herrera, Bartosz Krawczyk, Michal Wozniak, 2014, 2014 IEEE Symposium on Computational Intelligence and Data Mining (CIDM).

Melanoma Classification Based on Ensemble Classification of Dermoscopy Image Features

Gerald Schaefer, Aboul Ella Hassanien, Bartosz Krawczyk, 2014, AMLTA.

Cost-Sensitive Learning

Francisco Herrera, Mikel Galar, Salvador García, 2018 .

Improved Adaptive Splitting and Selection: the Hybrid Training Method of a Classifier Based on a Feature Space Partitioning

Bartosz Krawczyk, Michal Wozniak, Konrad Jackowski, 2014, Int. J. Neural Syst..

Instance exploitation for learning temporary concepts from sparsely labeled drifting data streams pdf

Bartosz Krawczyk, Lukasz Korycki, B. Krawczyk, 2020, Pattern Recognit..

An Empirical Insight Into Concept Drift Detectors Ensemble Strategies

Bartosz Krawczyk, Michal Wozniak, Pawel Ksieniewicz, 2018, 2018 IEEE Congress on Evolutionary Computation (CEC).

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

Bartosz Krawczyk, Michal Wozniak, Pawel Ksieniewicz, 2018, Neurocomputing.

Combining Active Learning and Self-Labeling for Data Stream Mining

Bartosz Krawczyk, Lukasz Korycki, B. Krawczyk, 2017, CORES.

Hybrid One-Class Ensemble for High-Dimensional Data Classification

Bartosz Krawczyk, 2016, ACIIDS.

Forming Ensembles of Soft One-Class Classifiers with Weighted Bagging

Bartosz Krawczyk, 2015, New Generation Computing.

Cost-sensitive decision tree ensembles for effective imbalanced classification

Gerald Schaefer, Bartosz Krawczyk, Michal Wozniak, 2014, Appl. Soft Comput..

Introduction to KDD and Data Science

Francisco Herrera, Mikel Galar, Salvador García, 2018 .

Tackling label noise with multi-class decomposition using fuzzy one-class support vector machines

Bartosz Krawczyk, Michal Wozniak, José A. Sáez, 2016, 2016 IEEE International Conference on Fuzzy Systems (FUZZ-IEEE).

Sentiment Classification from Multi-class Imbalanced Twitter Data Using Binarization

Bartosz Krawczyk, Bridget T. McInnes, Alberto Cano, 2017, HAIS.

An improved ensemble approach for imbalanced classification problems

Gerald Schaefer, Bartosz Krawczyk, 2013, 2013 IEEE 8th International Symposium on Applied Computational Intelligence and Informatics (SACI).

Online ensemble learning with abstaining classifiers for drifting and noisy data streams

Bartosz Krawczyk, Alberto Cano, B. Krawczyk, 2017, Appl. Soft Comput..

Hybrid Ensemble Machine Learning for Complex and Dynamic Data

Bartosz Krawczyk, Bogdan Trawinski, 2015, New Generation Computing.

Dimensionality Reduction for Imbalanced Learning

Francisco Herrera, Mikel Galar, Salvador García, 2018 .

Privacy Preserving Models of k-NN Algorithm

Bartosz Krawczyk, Michal Wozniak, B. Krawczyk, 2011, Computer Recognition Systems 4.

Hyperspectral Image Analysis Based on Color Channels and Ensemble Classifier

Bartosz Krawczyk, Michal Wozniak, Pawel Ksieniewicz, 2014, HAIS.

Workshop on Nonstationary Models of Pattern Recognition and Classifier Combinations

Bartosz Krawczyk, Michal Wozniak, 2016, ICCS.

Hyperspectral Image Analysis Based on Quad Tree Decomposition

Bartosz Krawczyk, Michal Wozniak, Pawel Ksieniewicz, 2014, SOCO-CISIS-ICEUTE.

GPU-Accelerated Extreme Learning Machines for Imbalanced Data Streams with Concept Drift

Bartosz Krawczyk, B. Krawczyk, 2016, ICCS.

The deterministic subspace method for constructing classifier ensembles

Bartosz Krawczyk, Michal Wozniak, Michal Koziarski, 2017, Pattern Analysis and Applications.

Analyzing the oversampling of different classes and types of examples in multi-class imbalanced datasets

Bartosz Krawczyk, Michal Wozniak, José A. Sáez, 2016, Pattern Recognit..

Active Learning with Abstaining Classifiers for Imbalanced Drifting Data Streams

Bartosz Krawczyk, Lukasz Korycki, Alberto Cano, 2019, 2019 IEEE International Conference on Big Data (Big Data).

Evolving rule-based classifiers with genetic programming on GPUs for drifting data streams

Bartosz Krawczyk, Alberto Cano, B. Krawczyk, 2019, Pattern Recognit..

Accuracy and diversity in classifier selection for one-class classification ensembles

Bartosz Krawczyk, Michal Wozniak, 2013, 2013 IEEE Symposium on Computational Intelligence and Ensemble Learning (CIEL).

Combined Classifiers with Neural Fuser for Spam Detection

Bartosz Krawczyk, Michal Wozniak, Marcin Zmyslony, 2012, CISIS/ICEUTE/SOCO Special Sessions.

Diversity measures for one-class classifier ensembles

Bartosz Krawczyk, Michal Wozniak, B. Krawczyk, 2014, Neurocomputing.

Learning Classification Rules with Differential Evolution for High-Speed Data Stream Mining on GPU s

Bartosz Krawczyk, Alberto Cano, B. Krawczyk, 2018, 2018 IEEE Congress on Evolutionary Computation (CEC).

Breast Thermogram Analysis Using Classifier Ensembles and Image Symmetry Features

Gerald Schaefer, Bartosz Krawczyk, B. Krawczyk, 2014, IEEE Systems Journal.

Effective Imbalanced Classification of Breast Thermogram Features

Gerald Schaefer, Bartosz Krawczyk, 2015, PReMI.

Selecting local ensembles for multi-class imbalanced data classification

Bartosz Krawczyk, Michal Wozniak, Alberto Cano, 2018, 2018 International Joint Conference on Neural Networks (IJCNN).

Dynamic classifier selection for one-class classification

Bartosz Krawczyk, Michal Wozniak, B. Krawczyk, 2016, Knowl. Based Syst..

Experiments on simultaneous combination rule training and ensemble pruning algorithm

Bartosz Krawczyk, Michal Wozniak, 2014, 2014 IEEE Symposium on Computational Intelligence in Ensemble Learning (CIEL).

A hybrid classifier committee for analysing asymmetry features in breast thermograms

Gerald Schaefer, Bartosz Krawczyk, 2014, Appl. Soft Comput..

Leveraging Ensemble Pruning for Imbalanced Data Classification

Bartosz Krawczyk, Michal Wozniak, B. Krawczyk, 2018, 2018 IEEE International Conference on Systems, Man, and Cybernetics (SMC).

One-class classifiers with incremental learning and forgetting for data streams with concept drift

Bartosz Krawczyk, Michał Woźniak, B. Krawczyk, 2015, Soft Comput..

Learning from Imbalanced Data Streams

Francisco Herrera, Mikel Galar, Salvador García, 2018 .

On the usefulness of one-class classifier ensembles for decomposition of multi-class problems

Francisco Herrera, Bartosz Krawczyk, Michal Wozniak, 2015, Pattern Recognit..

Incremental One-Class Bagging for Streaming and Evolving Big Data

Bartosz Krawczyk, Michal Wozniak, 2015, TrustCom 2015.

Combined Cleaning and Resampling Algorithm for Multi-Class Imbalanced Data with Label Noise pdf

Bartosz Krawczyk, Michal Koziarski, Michal Wo'zniak, 2020, Knowl. Based Syst..

Non-classical Imbalanced Classification Problems

Francisco Herrera, Mikel Galar, Salvador García, 2018 .

Combining active learning with concept drift detection for data stream mining

Bartosz Krawczyk, Michal Wozniak, Bernhard Pfahringer, 2018, 2018 IEEE International Conference on Big Data (Big Data).

Adaptive Splitting and Selection Algorithm for Classification of Breast Cytology Images

Bartosz Krawczyk, Michal Wozniak, Pawel Filipczuk, 2012, ICCCI.

Forming and pruning one-class classifier ensembles

Bartosz Krawczyk, B. Krawczyk, 2015 .

Multi-class imbalanced big data classification on Spark

Bartosz Krawczyk, IV WilliamC.Sleeman, B. Krawczyk, 2021, Knowl. Based Syst..

Recent Advances in Applied Computational Intelligence

Bartosz Krawczyk, Urszula Markowska-Kaczmar, Halina Kwasnicka, 2014, Appl. Artif. Intell..

Fast Case-Based Reasoning for Large-Scale Streaming Classification

Francisco Herrera, Bartosz Krawczyk, José Manuel Benítez, 2017 .

Breast thermogram analysis using a cost-sensitive multiple classifier system

Gerald Schaefer, Bartosz Krawczyk, Michal Wozniak, 2012, Proceedings of 2012 IEEE-EMBS International Conference on Biomedical and Health Informatics.

Bagging Using Instance-Level Difficulty for Multi-Class Imbalanced Big Data Classification on Spark

Bartosz Krawczyk, IV WilliamC.Sleeman, 2019, 2019 IEEE International Conference on Big Data (Big Data).

Combining nearest neighbour classifiers based on small subsamples for big data analytics

Bartosz Krawczyk, Michal Wozniak, B. Krawczyk, 2015, 2015 IEEE 2nd International Conference on Cybernetics (CYBCONF).

Data stream classification and big data analytics

Bartosz Krawczyk, Michal Wozniak, Jerzy Stefanowski, 2015, Neurocomputing.

One-Class Classification Decomposition for Imbalanced Classification of Breast Cancer Malignancy Data

Adam Krzyzak, Bartosz Krawczyk, Thomas Fevens, 2014, ICAISC.

Determination of changes in plasma structure during extracorporeal circulation - studies by ATR-FTIR spectroscopy and machine learning methods

Bartosz Krawczyk, Sylwia Olsztynska-Janus, Barbara Kmiecik, 2014, IWBBIO.

VOCs classification based on the committee of classifiers coupled with single sensor signals

Bartosz Krawczyk, Monika Maciejewska, Andrzej Szczurek, 2013 .

HEp-2 Cell Classification Using Multi-dimensional Local Binary Patterns and Ensemble Classification

Gerald Schaefer, Bartosz Krawczyk, Niraj P. Doshi, 2013, 2013 2nd IAPR Asian Conference on Pattern Recognition.

Ensemble of One-Dimensional Classifiers for Hyperspectral Image Analysis

Bartosz Krawczyk, Michal Wozniak, Pawel Ksieniewicz, 2016, DMBD.

Data Intrinsic Characteristics

Francisco Herrera, Mikel Galar, Salvador García, 2018 .

Local ensemble learning from imbalanced and noisy data for word sense disambiguation

Bartosz Krawczyk, Bridget T. McInnes, B. Krawczyk, 2017, Pattern Recognit..

Combined classifier based on feature space partitioning

Bartosz Krawczyk, Michal Wozniak, B. Krawczyk, 2012, Int. J. Appl. Math. Comput. Sci..

Oversampling Methods for Classification of Imbalanced Breast Cancer Malignancy Data

Adam Krzyzak, Bartosz Krawczyk, Thomas Fevens, 2012, ICCVG.

Imbalanced Classification for Big Data

Francisco Herrera, Mikel Galar, Salvador García, 2018 .

Instance reduction for one-class classification

Francisco Herrera, Salvador García, Bartosz Krawczyk, 2018, Knowledge and Information Systems.

Cost-sensitive one-vs-one ensemble for multi-class imbalanced data

Bartosz Krawczyk, 2016, 2016 International Joint Conference on Neural Networks (IJCNN).

Multidimensional data classification with chordal distance based kernel and Support Vector Machines

Bartosz Krawczyk, Michal Wozniak, Boguslaw Cyganek, 2015, Eng. Appl. Artif. Intell..

Diversity in Ensembles for One-Class Classification

Bartosz Krawczyk, B. Krawczyk, 2012, ADBIS Workshops.

On diversity measures for fuzzy one-class classifier ensembles

Bartosz Krawczyk, Michal Wozniak, B. Krawczyk, 2013, 2013 IEEE Symposium on Computational Intelligence and Ensemble Learning (CIEL).

Ensemble learning for data stream analysis: A survey

João Gama, Bartosz Krawczyk, Leandro L. Minku, 2017, Inf. Fusion.

Combining One-vs-One Decomposition and Ensemble Learning for Multi-class Imbalanced Data

Bartosz Krawczyk, 2015, CORES.

E-medical diagnosis support system for non-invasive liver fibrosis recognition

Bartosz Krawczyk, Tomasz Orczyk, Michal Wozniak, 2013, Stud. Inform. Univ..

Cost Sensitive Hierarchical Classifiers for Non-invasive Recognition of Liver Fibrosis Stage

Piotr Porwik, Bartosz Krawczyk, Michal Wozniak, 2013, CORES.

On optimal settings of classification tree ensembles for medical decision support

Bartosz Krawczyk, Mateusz Budnik, 2013, Health Informatics J..

Designing Cost-Sensitive Ensemble - Genetic Approach

Bartosz Krawczyk, Michal Wozniak, 2011, IP&C.

Foundations on Imbalanced Classification

Francisco Herrera, Mikel Galar, Salvador García, 2018 .

Analysis of Diversity Assurance Methods for Combined Classifiers

Bartosz Krawczyk, Michal Wozniak, 2012, IP&C.

Addressing the Overlapping Data Problem in Classification Using the One-vs-One Decomposition Strategy

Mikel Galar, Bartosz Krawczyk, José A. Sáez, 2019, IEEE Access.

Learning from Imbalanced Data Sets

Francisco Herrera, Mikel Galar, Salvador García, 2018, Springer International Publishing.

Empowering one-vs-one decomposition with ensemble learning for multi-class imbalanced data

Francisco Herrera, Bartosz Krawczyk, Salvador García, 2016, Knowl. Based Syst..

Fault diagnosis of marine 4-stroke diesel engines using a one-vs-one extreme learning ensemble

Bartosz Krawczyk, Michal Wozniak, Jerzy Kowalski, 2017, Eng. Appl. Artif. Intell..

An Analysis of Properties of Malignant Cases for Imbalanced Breast Thermogram Feature Classification

Gerald Schaefer, Bartosz Krawczyk, B. Krawczyk, 2013, 2013 2nd IAPR Asian Conference on Pattern Recognition.

Multi-class Imbalanced Data Oversampling for Vertebral Column Pathologies Classification

Héctor Quintián-Pardo, Bartosz Krawczyk, Emilio Corchado, 2018, HAIS.

Cost-Sensitive Perceptron Decision Trees for Imbalanced Drifting Data Streams

Bartosz Krawczyk, Przemyslaw Skryjomski, 2017, ECML/PKDD.

Combining Diverse One-Class Classifiers

Bartosz Krawczyk, Michal Wozniak, B. Krawczyk, 2012, HAIS.

Uniqueness of Medical Data Mining: How the new technologies and data they generate are transforming medicine pdf

Bartosz Krawczyk, Kevin J. Staley, Krzysztof J. Cios, 2019, ArXiv.

A Survey of Big Data Issues in Electronic Health Record Analysis

Piotr Porwik, Manuel Graña, Bartosz Krawczyk, 2016, Appl. Artif. Intell..

One-class classifier ensemble pruning and weighting with firefly algorithm

Bartosz Krawczyk, B. Krawczyk, 2015, Neurocomputing.

Reacting to different types of concept drift with adaptive and incremental one-class classifiers

Bartosz Krawczyk, Michal Wozniak, B. Krawczyk, 2015, 2015 IEEE 2nd International Conference on Cybernetics (CYBCONF).

Clustering-Based Ensemble of One-Class Classifiers for Hyperspectral Image Segmentation

Bartosz Krawczyk, Michal Wozniak, Boguslaw Cyganek, 2014, HAIS.

DIVERSITY-BASED CLASSIFIER SELECTION FOR BREAST CANCER CYTOLOGICAL IMAGE ANALYSIS

Bartosz Krawczyk, Andrzej Obuchowicz, Michał Woźniak, 2014 .

Nearest Neighbor Classification for High-Speed Big Data Streams Using Spark

Sergio Ramírez-Gallego, Bartosz Krawczyk, José Manuel Benítez, 2017, IEEE Transactions on Systems, Man, and Cybernetics: Systems.

An ensemble classification approach for melanoma diagnosis

Gerald Schaefer, Bartosz Krawczyk, Hitoshi Iyatomi, 2014, Memetic Computing.

Optimization Algorithms for One-Class Classification Ensemble Pruning

Bartosz Krawczyk, Michal Wozniak, 2014, ACIIDS.

Addressing Local Class Imbalance in Balanced Datasets with Dynamic Impurity Decision Trees

Bartosz Krawczyk, Andriy Mulyar, 2018, DS.

One-Class Classification Ensemble with Dynamic Classifier Selection

Bartosz Krawczyk, Michal Wozniak, B. Krawczyk, 2014, ISNN.

Evolutionary undersampling boosting for imbalanced classification of breast cancer malignancy

Mikel Galar, Bartosz Krawczyk, Francisco Herrera, 2016, Appl. Soft Comput..

APPLICATION OF ADAPTIVE SPLITTING AND SELECTION CLASSIFIER TO THE SPAM FILTERING PROBLEM

Bartosz Krawczyk, Michal Wozniak, Konrad Jackowski, 2013, Cybern. Syst..

New untrained aggregation methods for classifier combination

Bartosz Krawczyk, Michal Wozniak, 2014, 2014 International Joint Conference on Neural Networks (IJCNN).

Incremental One-Class Bagging for Streaming and Evolving Big Data

Bartosz Krawczyk, Michal Wozniak, B. Krawczyk, 2015, 2015 IEEE Trustcom/BigDataSE/ISPA.

Influence of minority class instance types on SMOTE imbalanced data oversampling

Bartosz Krawczyk, Przemyslaw Skryjomski, B. Krawczyk, 2017, LIDTA@PKDD/ECML.

Untrained weighted classifier combination with embedded ensemble pruning

Bartosz Krawczyk, Michal Wozniak, B. Krawczyk, 2016, Neurocomputing.

Speeding up k-Nearest Neighbors classifier for large-scale multi-label learning on GPUs

Bartosz Krawczyk, Alberto Cano, Przemyslaw Skryjomski, 2019, Neurocomputing.

Improved LBP texture classification using ensemble learning

Gerald Schaefer, Bartosz Krawczyk, Niraj P. Doshi, 2013, 2013 IEEE International Conference on Multimedia and Expo (ICME).

Online query by committee for active learning from drifting data streams

Bartosz Krawczyk, Michal Wozniak, B. Krawczyk, 2017, 2017 International Joint Conference on Neural Networks (IJCNN).

Adaptive Splitting and Selection ensemble for breast cancer malignancy grading

Bartosz Krawczyk, Michal Wozniak, Lukasz Jelen, 2014, 2014 IEEE Symposium on Computational Intelligence in Healthcare and e-health (CICARE).

Adaptive Splitting and Selection Method for Noninvasive Recognition of Liver Fibrosis Stage

Piotr Porwik, Bartosz Krawczyk, Michal Wozniak, 2013, ACIIDS.

Adversarial concept drift detection under poisoning attacks for robust data stream mining pdf

Bartosz Krawczyk, Lukasz Korycki, B. Krawczyk, 2020, Machine Learning.

Designing a compact Genetic fuzzy rule-based system for one-class classification

Francisco Herrera, Ana M. Sánchez, Bartosz Krawczyk, 2014, 2014 IEEE International Conference on Fuzzy Systems (FUZZ-IEEE).

Data Level Preprocessing Methods

Francisco Herrera, Mikel Galar, Salvador García, 2018 .

On the Influence of Class Noise in Medical Data Classification: Treatment Using Noise Filtering Methods

Bartosz Krawczyk, Michal Wozniak, José A. Sáez, 2016, Appl. Artif. Intell..

Incremental weighted one-class classifier for mining stationary data streams

Bartosz Krawczyk, Michal Wozniak, B. Krawczyk, 2015, J. Comput. Sci..

Clustering-Driven and Dynamically Diversified Ensemble for Drifting Data Streams

Bartosz Krawczyk, Lukasz Korycki, 2018, 2018 IEEE International Conference on Big Data (Big Data).

Evolutionary Cost-Sensitive Ensemble for Malware Detection

Bartosz Krawczyk, Michal Wozniak, 2014, SOCO-CISIS-ICEUTE.

Handling Label Noise in Microarray Classification with One-Class Classifier Ensemble

Bartosz Krawczyk, Michal Wozniak, B. Krawczyk, 2014, ICT Innovations.

Imbalanced Classification with Multiple Classes

Francisco Herrera, Mikel Galar, Salvador García, 2018 .

Dynamic ensemble selection for multi-class classification with one-class classifiers

Francisco Herrera, Humberto Bustince, Mikel Galar, 2018, Pattern Recognit..

Experiments on distance measures for combining one-class classifiers

Bartosz Krawczyk, Michal Wozniak, 2012, 2012 Federated Conference on Computer Science and Information Systems (FedCSIS).

Scleroderma capillary pattern identification using texture descriptors and ensemble classification

Gerald Schaefer, Bartosz Krawczyk, Arcangelo Merla, 2013, 2013 35th Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC).

Algorithm-Level Approaches

Francisco Herrera, Mikel Galar, Salvador García, 2018 .

Radial-Based Approach to Imbalanced Data Oversampling

Bartosz Krawczyk, Michal Wozniak, Michal Koziarski, 2017, HAIS.

An evaluation of classifier ensembles for class imbalance problems

Gerald Schaefer, Bartosz Krawczyk, Michał Wozniak, 2013, 2013 International Conference on Informatics, Electronics and Vision (ICIEV).

Pruning One-Class Classifier Ensembles by Combining Sphere Intersection and Consistency Measures

Bartosz Krawczyk, Michal Wozniak, B. Krawczyk, 2013, ICAISC.

Immersive browsing in an image sphere

Gerald Schaefer, Bartosz Krawczyk, Mateusz Budnik, 2017, IMCOM.

A cost-sensitive ensemble classifier for breast cancer classification

Gerald Schaefer, Bartosz Krawczyk, Michal Wozniak, 2013, 2013 IEEE 8th International Symposium on Applied Computational Intelligence and Informatics (SACI).

Weighted Naïve Bayes Classifier with Forgetting for Drifting Data Streams

Bartosz Krawczyk, Michal Wozniak, B. Krawczyk, 2015, 2015 IEEE International Conference on Systems, Man, and Cybernetics.

Incremental Learning and Forgetting in One-Class Classifiers for Data Streams

Bartosz Krawczyk, Michal Wozniak, B. Krawczyk, 2013, CORES.

Cytological image analysis with firefly nuclei detection and hybrid one-class classification decomposition

Bartosz Krawczyk, Pawel Filipczuk, B. Krawczyk, 2014, Eng. Appl. Artif. Intell..

Active and adaptive ensemble learning for online activity recognition from data streams

Bartosz Krawczyk, B. Krawczyk, 2017, Knowl. Based Syst..

Cost-Sensitive Neural Network with ROC-Based Moving Threshold for Imbalanced Classification

Bartosz Krawczyk, Michal Wozniak, B. Krawczyk, 2015, IDEAL.

Untrained Method for Ensemble Pruning and Weighted Combination

Bartosz Krawczyk, Michal Wozniak, 2014, ISNN.

Cost-sensitive texture classification

Gerald Schaefer, Tomoharu Nakashima, Bartosz Krawczyk, 2014, 2014 IEEE Congress on Evolutionary Computation (CEC).

Hypertension Type Classification Using Hierarchical Ensemble of One-Class Classifiers for Imbalanced Data

Bartosz Krawczyk, Michal Wozniak, 2014, ICT Innovations.

On the Role of Cost-Sensitive Learning in Imbalanced Data Oversampling

Bartosz Krawczyk, Michal Wozniak, 2019, ICCS.

A Machine Learning method for relabeling arbitrary DICOM structure sets to TG-263 defined labels

Bartosz Krawczyk, Rishabh Kapoor, Preetam Ghosh, 2020, J. Biomed. Informatics.

AUTOMATIC DETECTION AND COUNTING OF PLATELETS IN MICROSCOPIC IMAGE

Bartosz Krawczyk, Robert Burduk, B. Krawczyk, 2010 .

Data Classification with Ensembles of One-Class Support Vector Machines and Sparse Nonnegative Matrix Factorization

Bartosz Krawczyk, Boguslaw Cyganek, B. Cyganek, 2015, ACIIDS.

Influence of Distance Measures on the Effectiveness of One-Class Classification Ensembles

Bartosz Krawczyk, Michal Wozniak, 2014, Appl. Artif. Intell..

Learning with Imbalanced Domains: Preface

Luís Torgo, Bartosz Krawczyk, Nuno Moniz, 2017, LIDTA@PKDD/ECML.

Classifier ensemble for an effective cytological image analysis

Bartosz Krawczyk, Michal Wozniak, Pawel Filipczuk, 2013, Pattern Recognit. Lett..

Weighted One-Class Classifier Ensemble Based on Fuzzy Feature Space Partitioning

Bartosz Krawczyk, Michal Wozniak, Boguslaw Cyganek, 2014, 2014 22nd International Conference on Pattern Recognition.

Wagging for Combining Weighted One-class Support Vector Machines

Bartosz Krawczyk, Michal Wozniak, B. Krawczyk, 2015, ICCS.

Adaptive Ensemble Active Learning for Drifting Data Stream Mining

Bartosz Krawczyk, Alberto Cano, B. Krawczyk, 2019, IJCAI.

Radial-Based Oversampling for Multiclass Imbalanced Data Classification

Bartosz Krawczyk, Michal Koziarski, Michal Wozniak, 2020, IEEE Transactions on Neural Networks and Learning Systems.

2nd Workshop on Learning with Imbalanced Domains: Preface

Stan Matwin, Luís Torgo, Bartosz Krawczyk, 2018, LIDTA@ECML/PKDD.

Pruning Ensembles of One-Class Classifiers with X-means Clustering

Bartosz Krawczyk, Michal Wozniak, 2015, ACIIDS.

A pruned ensemble classifier for effective breast thermogram analysis

Gerald Schaefer, Bartosz Krawczyk, 2013, 2013 35th Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC).

Forming classifier ensembles with deterministic feature subspaces

Bartosz Krawczyk, Michal Wozniak, Michal Koziarski, 2016, 2016 Federated Conference on Computer Science and Information Systems (FedCSIS).

Monotonic classification: an overview on algorithms, performance measures and data sets

Pedro Antonio Gutiérrez, José Ramón Cano, Salvador García, 2018, Neurocomputing.

Cost-Sensitive Splitting and Selection Method for Medical Decision Support System

Bartosz Krawczyk, Michal Wozniak, Konrad Jackowski, 2012, IDEAL.

A hybrid cost-sensitive ensemble for imbalanced breast thermogram classification

Gerald Schaefer, Bartosz Krawczyk, Michal Wozniak, 2015, Artif. Intell. Medicine.

Unsupervised Drift Detector Ensembles for Data Stream Mining

Bartosz Krawczyk, Lukasz Korycki, B. Krawczyk, 2019, 2019 IEEE International Conference on Data Science and Advanced Analytics (DSAA).

Breast Cancer Identification Based on Thermal Analysis and a Clustering and Selection Classification Ensemble

Gerald Schaefer, Bartosz Krawczyk, Shao Ying Zhu, 2013, Brain and Health Informatics.

Distributed Privacy-Preserving Minimal Distance Classification

Bartosz Krawczyk, Michal Wozniak, B. Krawczyk, 2013, HAIS.

Combining one-class support vector machines for microarray classification

Bartosz Krawczyk, 2013, 2013 Federated Conference on Computer Science and Information Systems.

Pruning Ensembles with Cost Constraints

Bartosz Krawczyk, Michal Wozniak, 2015, ACIIDS.

Effective multiple classifier systems for breast thermogram analysis

Gerald Schaefer, Bartosz Krawczyk, 2012, Proceedings of the 21st International Conference on Pattern Recognition (ICPR2012).

Adaptive Deep Forest for Online Learning from Drifting Data Streams pdf

Bartosz Krawczyk, Lukasz Korycki, B. Krawczyk, 2020, ArXiv.

Online Oversampling for Sparsely Labeled Imbalanced and Non-Stationary Data Streams

Bartosz Krawczyk, Lukasz Korycki, B. Krawczyk, 2020, 2020 International Joint Conference on Neural Networks (IJCNN).

Software and Libraries for Imbalanced Classification

Francisco Herrera, Mikel Galar, Salvador García, 2018 .

Multi-Label Punitive kNN with Self-Adjusting Memory for Drifting Data Streams

Bartosz Krawczyk, Alberto Cano, Martha Roseberry, 2019, ACM Trans. Knowl. Discov. Data.

Radial-Based oversampling for noisy imbalanced data classification

Bartosz Krawczyk, Michal Wozniak, Michal Koziarski, 2019, Neurocomputing.

Synthetic Oversampling with the Majority Class: A New Perspective on Handling Extreme Imbalance

Osmar R. Zaïane, Bartosz Krawczyk, Nathalie Japkowicz, 2018, 2018 IEEE International Conference on Data Mining (ICDM).

Miłosz i Andrzejewski - trudny dialog / Bartosz Krawczyk.

Bartosz Krawczyk, 2011 .

Selecting locally specialised classifiers for one-class classification ensembles

Bartosz Krawczyk, Boguslaw Cyganek, B. Cyganek, 2017, Pattern Analysis and Applications.

Melanoma Classification Using Dermoscopy Imaging and Ensemble Learning

Gerald Schaefer, Bartosz Krawczyk, Hitoshi Iyatomi, 2013, 2013 2nd IAPR Asian Conference on Pattern Recognition.

Undersampling with Support Vectors for Multi-Class Imbalanced Data Classification

Bartosz Krawczyk, Nathalie Japkowicz, Roberto Corizzo, 2021, 2021 International Joint Conference on Neural Networks (IJCNN).

Tensor decision trees for continual learning from drifting data streams

Bartosz Krawczyk, B. Krawczyk, 2021, Machine Learning.

Class-Incremental Experience Replay for Continual Learning under Concept Drift

Bartosz Krawczyk, Lukasz Korycki, B. Krawczyk, 2021, 2021 IEEE/CVF Conference on Computer Vision and Pattern Recognition Workshops (CVPRW).

Imbalanced Big Data Oversampling: Taxonomy, Algorithms, Software, Guidelines and Future Directions pdf

Bartosz Krawczyk, IV WilliamC.Sleeman, 2021, ArXiv.

Self-adjusting k nearest neighbors for continual learning from multi-label drifting data streams

Bartosz Krawczyk, Alberto Cano, Youcef Djenouri, 2021, Neurocomputing.

On the combined effect of class imbalance and concept complexity in deep learning

Bartosz Krawczyk, Nathalie Japkowicz, Roberto Corizzo, 2021, 2021 IEEE International Conference on Big Data (Big Data).

Low-Dimensional Representation Learning from Imbalanced Data Streams

Bartosz Krawczyk, Lukasz Korycki, 2021, PAKDD.

DeepSMOTE: Fusing Deep Learning and SMOTE for Imbalanced Data

Nitesh V. Chawla, Bartosz Krawczyk, Damien Dablain, 2021, IEEE Transactions on Neural Networks and Learning Systems.

Locally Linear Support Vector Machines for Imbalanced Data Classification

Bartosz Krawczyk, Alberto Cano, B. Krawczyk, 2021, PAKDD.

Streaming Decision Trees for Lifelong Learning

Bartosz Krawczyk, Lukasz Korycki, B. Krawczyk, 2021, ECML/PKDD.

XRRpred: accurate predictor of crystal structure quality from protein sequence

Lukasz Kurgan, Bartosz Krawczyk, Sina Ghadermarzi, 2021, Bioinform..

Tensor Decision Trees for Continual Learning from Drifting Data Streams

Bartosz Krawczyk, 2021, 2021 IEEE 8th International Conference on Data Science and Advanced Analytics (DSAA).

Evaluating and Explaining Generative Adversarial Networks for Continual Learning under Concept Drift

Bartosz Krawczyk, Michał Woźniak, Filip Guzy, 2021, 2021 International Conference on Data Mining Workshops (ICDMW).

Mining Drifting Data Streams on a Budget: Combining Active Learning with Self-Labeling pdf

Bartosz Krawczyk, Lukasz Korycki, 2021, ArXiv.

Concept Drift Detection from Multi-Class Imbalanced Data Streams

Bartosz Krawczyk, Lukasz Korycki, 2021, 2021 IEEE 37th International Conference on Data Engineering (ICDE).

Pattern recognition approach to classifying CYP 2C19 isoform

Bartosz Krawczyk, B. Krawczyk, 2012 .

Automatic diagnosis of primary headaches by machine learning methods

Bartosz Krawczyk, Dragan Simić, Svetlana Simić, 2013 .