Reprint

Ensemble Algorithms and Their Applications

Edited by
September 2020
182 pages
  • ISBN978-3-03936-958-4 (Hardback)
  • ISBN978-3-03936-959-1 (PDF)

This is a Reprint of the Special Issue Ensemble Algorithms and Their Applications that was published in

Computer Science & Mathematics
Summary

In recent decades, the development of ensemble learning methodologies has gained a significant attention from the scientific and industrial community, and found their application in various real-word problems. Theoretical and experimental evidence proved that ensemble models provide a considerably better prediction performance than single models. The main aim of this collection is to present the recent advances related to ensemble learning algorithms and investigate the impact of their application in a diversity of real-world problems. All papers possess significant elements of novelty and introduce interesting ensemble-based approaches, which provide readers with a glimpse of the state-of-the-art research in the domain.

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