Krystyna Napierala

According to our database1, Krystyna Napierala authored at least 15 papers between 2010 and 2017.

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Bibliography

2017
Evaluating Difficulty of Multi-class Imbalanced Data.
Proceedings of the Foundations of Intelligent Systems - 23rd International Symposium, 2017

2016
Types of minority class examples and their influence on learning classifiers from imbalanced data.
J. Intell. Inf. Syst., 2016

Post-processing of BRACID Rules Induced from Imbalanced Data.
Fundam. Informaticae, 2016

A Jamming-Resilient MAC-layer Device Identification for Internet of Things.
CoRR, 2016

Increasing the Interpretability of Rules Induced from Imbalanced Data by Using Bayesian Confirmation Measures.
Proceedings of the New Frontiers in Mining Complex Patterns - 5th International Workshop, 2016

2015
Abstaining in rule set bagging for imbalanced data.
Log. J. IGPL, 2015

Addressing imbalanced data with argument based rule learning.
Expert Syst. Appl., 2015

2014
Local Characteristics of Minority Examples in Pre-processing of Imbalanced Data.
Proceedings of the Foundations of Intelligent Systems - 21st International Symposium, 2014

2012
BRACID: a comprehensive approach to learning rules from imbalanced data.
J. Intell. Inf. Syst., 2012

Modifications of Classification Strategies in Rule Set Based Bagging for Imbalanced Data.
Proceedings of the Hybrid Artificial Intelligent Systems - 7th International Conference, 2012

Identification of Different Types of Minority Class Examples in Imbalanced Data.
Proceedings of the Hybrid Artificial Intelligent Systems - 7th International Conference, 2012

2011
Efficient Isosurface Extraction Using Marching Tetrahedra and Histogram Pyramids on Multiple GPUs.
Proceedings of the Parallel Processing and Applied Mathematics, 2011

Human Re-identification System on Highly Parallel GPU and CPU Architectures.
Proceedings of the Multimedia Communications, Services and Security, 2011

2010
Learning from Imbalanced Data in Presence of Noisy and Borderline Examples.
Proceedings of the Rough Sets and Current Trends in Computing, 2010

Argument Based Generalization of MODLEM Rule Induction Algorithm.
Proceedings of the Rough Sets and Current Trends in Computing, 2010


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