Low sample scenarios are present in other research domains and still attract interest in developing new techniques to combat data scarcity. A method based on ...
Jan 22, 2016 · We empirically examine several model selection criteria coupled with new model combining approaches that were recently proposed. The results ...
Comparison of Combining Methods using Extreme Learning Machines under Small Sample Scenario. Author. Dušan Sovilj · Kaj Mikael Björk · Amaury Lendasse, Missouri ...
Comparison of combining methods using Extreme Learning Machines under small sample scenario · List of references · Publications that cite this publication.
Comparison of combining methods using Extreme Learning Machines under small sample scenario ; A genetic algorithm-based virtual sample generation technique to ...
Comparison of combining methods using Extreme Learning Machines under small sample scenario. Dusan Sovilj, Kaj-Mikael Björk, Amaury Lendasse. Finance, Helsinki.
This paper studies the effectiveness of the ELM ensemble models in solving small sample-sized classification problems. The research involves two variants of the ...
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May 22, 2021 · Extreme learning machine (ELM) is a training algorithm for single hidden layer feedforward neural network (SLFN), which converges much faster than traditional ...
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[182, 188] also corroborated the findings that the ELM approach was superior in terms of generalization and computational economy. Yet another research group, ...
May 25, 2022 · In this study, we propose a novel key features screening method based on extreme learning machine (KFS-ELM) to screen key features of AD. It is ...