Ensemble model of Artificial Neural Networks with randomized number of hidden neurons
Conventional artificial intelligence techniques and their hybrid models are incapable of handling several hypotheses at a time. The limitation in the performance of certain techniques has made the ensemble learning paradigm a desirable alternative for better predictions. The petroleum industry stand...
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Main Authors: | , |
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Format: | Conference or Workshop Item |
Language: | English |
Published: |
2013
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Subjects: | |
Online Access: | http://ir.unimas.my/id/eprint/8474/1/Ensemble%20model%20of%20non-linear%20feature%20selection-based%20Extreme%20Learning%20Machine%20%28abstract%29.pdf http://ir.unimas.my/id/eprint/8474/ http://ieeexplore.ieee.org/xpl/articleDetails.jsp?arnumber=6637562 |
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Institution: | Universiti Malaysia Sarawak |
Language: | English |