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Chapter and Conference Paper
Incremental Extreme Learning Machine for Binary Data Stream Classification
Classifier ensembles have shown the ability to classify drifted data streams. The following paper proposes an ensemble consisting of a single hidden layer feedforward neural network and an Extreme Learning Mac...
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Chapter and Conference Paper
SWAROG Project Approach to Fake News Detection Problem
We often come across the seemingly obvious remark that the modern world is full of data. From the perspective of a regular Internet user, we perceive this as an abundance of content that we unintentionally con...
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Chapter and Conference Paper
Analysis of the Possibility to Employ Relationship Between the Problem Complexity and the Classification Quality as Model Optimization Proxy
Bulk construction of pattern classifiers, whether for optimizing input data configurations or method hyperparameters, is a computationally highly complex task. The main problem is the prediction quality evalua...
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Chapter and Conference Paper
Analysis of Extractive Text Summarization Methods as a Binary Classification Problem
One of the critical challenges for natural language processing methods is the issue of automatic content summarization. The enormous increase in the amount of data delivered to users by news services leads to ...