| Keywords
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Deep learning, Staked ensemble, Statistics +
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| Level
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Master +
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| OneLineSummary
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This project aims at training multiple parallel deep networks in such a way to learn different representation of data which will be suitable to frame these networks in stacked ensemble framework. +
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| Prerequisites
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deep learning, data mining,
programming knowledge of one of deep learning frameworks such as tensorflow, pytorch or at least their APIs +
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| References
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1- David H.Wolpert, "Stacked generalisatio … 1- David H.Wolpert, "Stacked generalisation" https://doi.org/10.1016/S0893-6080(05)80023-1
2- Jason Brownle, "How to Develop a Stacking Ensemble for Deep Learning Neural Networks in Python With Keras", https://machinelearningmastery.com/stacking-ensemble-for-deep-learning-neural-networks/
3 - PS Mashhadi, S Nowaczyk, S Pashami. "Parallel orthogonal deep neural network" Neural Networks 140, 167-183ural network" Neural Networks 140, 167-183
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| StudentProjectStatus
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Open +
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| Supervisors
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Sławomir Nowaczyk +
, Peyman Mashhadi +
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| TimeFrame
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Fall 2022 +
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| Title
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Deep stacked ensemble +
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| Categories |
StudentProject +
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| Modification dateThis property is a special property in this wiki.
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17 September 2022 16:52:09 +
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