2 citations · 6 across the 9 of their papers we have counts for
6 papers · 1 filter
Structuring the Processing Frameworks for Data Stream Evaluation and Application
Joanna Komorniczak, Paweł Ksieniewicz, Paweł Zyblewski
The following work addresses the problem of frameworks for data stream processing that can be used to evaluate the solutions in an environment that resembles real-world application…
Unsupervised Concept Drift Detection based on Parallel Activations of Neural Network
Joanna Komorniczak, Paweł Ksieniewicz
Practical applications of artificial intelligence increasingly often have to deal with the streaming properties of real data, which, considering the time factor, are subject to phe…
Taking Class Imbalance Into Account in Open Set Recognition Evaluation
Joanna Komorniczak, Pawel Ksieniewicz
In recent years Deep Neural Network-based systems are not only increasing in popularity but also receive growing user trust. However, due to the closed-world assumption of such sys…
torchosr -- a PyTorch extension package for Open Set Recognition models evaluation in Python
Joanna Komorniczak, Pawel Ksieniewicz
The article presents the torchosr package - a Python package compatible with PyTorch library - offering tools and methods dedicated to Open Set Recognition in Deep Neural Networks.…
problexity -- an open-source Python library for binary classification problem complexity assessment
Joanna Komorniczak, Pawel Ksieniewicz
The classification problem's complexity assessment is an essential element of many topics in the supervised learning domain. It plays a significant role in meta-learning -- becomin…
Active Weighted Aging Ensemble for Drifted Data Stream Classification
Michał Woźniak, Paweł Zyblewski, Paweł Ksieniewicz
One of the significant problems of streaming data classification is the occurrence of concept drift, consisting of the change of probabilistic characteristics of the classification…