Lukasz Wróbel

Pawel Matyszok

Inf. Sci., 2022

Separate and conquer heuristic allows robust mining of contrast sets from various types of data.

[BibT_eX]

[DOI]

CoRR, 2022

MAINE: a web tool for multi-omics feature selection and rule-based data exploration.

[BibT_eX]

[DOI]

Bioinform., 2022

Demand forecasting in the fashion business - an example of customized nearest neighbour and linear mixed model approaches.

[BibT_eX]

[DOI]

Proceedings of the 17th Conference on Computer Science and Intelligence Systems, 2022

2020

Bone marrow transplant: children.

[BibT_eX]

[DOI]

Dataset, April, 2020

RuleKit: A comprehensive suite for rule-based learning.

[BibT_eX]

[DOI]

Knowl. Based Syst., 2020

2019

GuideR: A guided separate-and-conquer rule learning in classification, regression, and survival settings.

[BibT_eX]

[DOI]

Knowl. Based Syst., 2019

Detection of the Oocyte Orientation for the ICSI Method Automation.

[BibT_eX]

[DOI]

Magdalena Mazur-Milecka

Proceedings of the 12th International Conference on Human System Interaction, 2019

Fuzzy Modelling of the Methane Hazard Rate.

[BibT_eX]

[DOI]

Proceedings of the Beyond Databases, Architectures and Structures. Paving the Road to Smart Data Processing and Analysis, 2019

2018

A framework for learning and embedding multi-sensor forecasting models into a decision support system: A case study of methane concentration in coal mines.

[BibT_eX]

[DOI]

Inf. Sci., 2018

Bidirectional Action Rule Learning.

[BibT_eX]

[DOI]

Pawel Matyszok

Proceedings of the Computer and Information Sciences - 32nd International Symposium, 2018

Covering Approach to Action Rule Learning.

[BibT_eX]

[DOI]

Pawel Matyszok

Proceedings of the Beyond Databases, Architectures and Structures. Facing the Challenges of Data Proliferation and Growing Variety, 2018

EYE: Big Data System Supporting Preventive and Predictive Maintenance of Robotic Production Lines.

[BibT_eX]

[DOI]

Proceedings of the Beyond Databases, Architectures and Structures. Facing the Challenges of Data Proliferation and Growing Variety, 2018

The Use of Distributed Data Storage and Processing Systems in Bioinformatic Data Analysis.

[BibT_eX]

[DOI]

Proceedings of the Beyond Databases, Architectures and Structures. Facing the Challenges of Data Proliferation and Growing Variety, 2018

2017

Predicting seismic events in coal mines based on underground sensor measurements.

[BibT_eX]

[DOI]

Eng. Appl. Artif. Intell., 2017

Learning rule sets from survival data.

[BibT_eX]

[DOI]

BMC Bioinform., 2017

Decision Rule Learning from Stream of Measurements - A Case Study in Methane Hazard Forecasting in Coal Mines.

[BibT_eX]

[DOI]

Proceedings of the Man-Machine Interactions 5, 2017

2016

Rule Quality Measures Settings in Classification, Regression and Survival Rule Induction - an Empirical Approach.

[BibT_eX]

[DOI]

Marcin Michalak

Fundam. Informaticae, 2016

Outlier Detection and Elimination in Stream Data - An Experimental Approach.

[BibT_eX]

[DOI]

Proceedings of the Rough Sets - International Joint Conference, 2016

Data Intensive vs Sliding Window Outlier Detection in the Stream Data - An Experimental Approach.

[BibT_eX]

[DOI]

Proceedings of the Artificial Intelligence and Soft Computing, 2016

Application of RapidMiner and R Environments to Dangerous Seismic Events Prediction.

[BibT_eX]

[DOI]

Proceedings of the 2016 Federated Conference on Computer Science and Information Systems, 2016

Predicting Dangerous Seismic Events: AAIA'16 Data Mining Challenge.

[BibT_eX]

[DOI]

Proceedings of the 2016 Federated Conference on Computer Science and Information Systems, 2016

Influence of Outliers Introduction on Predictive Models Quality.

[BibT_eX]

[DOI]

Proceedings of the Beyond Databases, Architectures and Structures. Advanced Technologies for Data Mining and Knowledge Discovery, 2016

2015

Mining Data from Coal Mines: IJCRS'15 Data Challenge.

[BibT_eX]

[DOI]

Proceedings of the Rough Sets, Fuzzy Sets, Data Mining, and Granular Computing, 2015

Rule quality measures settings in a sequential covering rule induction algorithm - an empirical approach.

[BibT_eX]

[DOI]

Marcin Michalak

Proceedings of the 2015 Federated Conference on Computer Science and Information Systems, 2015

DISESOR - decision support system for mining industry.

[BibT_eX]

[DOI]

Michal Kozielski

Proceedings of the 2015 Federated Conference on Computer Science and Information Systems, 2015

Regression Rule Learning for Methane Forecasting in Coal Mines.

[BibT_eX]

[DOI]

Proceedings of the Beyond Databases, Architectures and Structures, 2015

2013

seismic-bumps.

[BibT_eX]

[DOI]

Dataset, April, 2013

Data-driven adaptive selection of rule quality measures for improving rule induction and filtration algorithms.

[BibT_eX]

[DOI]

Int. J. Gen. Syst., 2013

2012

Algorithms for Filtration of Unordered Sets of Regression Rules.

[BibT_eX]

[DOI]

Adam Skowron

Proceedings of the Multi-disciplinary Trends in Artificial Intelligence, 2012

Rule Quality Measure-Based Induction of Unordered Sets of Regression Rules.

[BibT_eX]

[DOI]

Adam Skowron

Proceedings of the Artificial Intelligence: Methodology, Systems, and Applications, 2012

2011

Data-Driven Adaptive Selection of Rules Quality Measures for Improving the Rules Induction Algorithm.

[BibT_eX]

[DOI]