publication . Preprint . Part of book or chapter of book . 2018

Deep Super Learner: A Deep Ensemble for Classification Problems

Steven Young; Tamer Abdou; Ayse Bener;
Open Access English
  • Published: 06 Mar 2018
Abstract
Deep learning has become very popular for tasks such as predictive modeling and pattern recognition in handling big data. Deep learning is a powerful machine learning method that extracts lower level features and feeds them forward for the next layer to identify higher level features that improve performance. However, deep neural networks have drawbacks, which include many hyper-parameters and infinite architectures, opaqueness into results, and relatively slower convergence on smaller datasets. While traditional machine learning algorithms can address these drawbacks, they are not typically capable of the performance levels achieved by deep neural networks. To ...
Subjects
arXiv: Computer Science::Machine Learning
free text keywords: Computer Science - Learning, Statistics - Machine Learning, Deep learning, Big data, business.industry, business, Ensemble learning, Transparency (graphic), Deep neural networks, Artificial neural network, Machine learning, computer.software_genre, computer, Artificial intelligence, Computer science, Convergence (routing)
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publication . Preprint . Part of book or chapter of book . 2018

Deep Super Learner: A Deep Ensemble for Classification Problems

Steven Young; Tamer Abdou; Ayse Bener;