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In this paper, combining the ideas of ensemble learning, online learning and deep learning, we propose a novel deep learning method called deep error-correcting output codes (DeepECOCs). DeepECOCs are composed of multiple layers of the ECOC module, which combines several incremental support vector machines (incremental SVMs) as base classifiers. In this novel deep architecture, each ECOC module can be considered as two successive layers of the network, while the incremental SVMs can be viewed as weighted links between two successive layers. In the pre-training procedure, supervisory information, i.e., class labels, can be used during the network initialization. The incremental SVMs lead this procedure to be very efficient, especially for large-scale applications. We have conducted extensive experiments to compare DeepECOCs with traditional ECOC, feature learning and deep learning algorithms. The results demonstrate that DeepECOCs perform, not only better than existing ECOC and feature learning algorithms, but also related to deep learning ones in most cases.<\/jats:p>","DOI":"10.3390\/a16120555","type":"journal-article","created":{"date-parts":[[2023,12,4]],"date-time":"2023-12-04T07:59:31Z","timestamp":1701676771000},"page":"555","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":5,"title":["Deep Error-Correcting Output Codes"],"prefix":"10.3390","volume":"16","author":[{"given":"Li-Na","family":"Wang","sequence":"first","affiliation":[{"name":"Qingdao Vocational and Technical College of Hotel Management, Qingdao 266100, China"}]},{"given":"Hongxu","family":"Wei","sequence":"additional","affiliation":[{"name":"College of Computer Science and Technology, Ocean University of China, Qingdao 266404, China"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-3093-6929","authenticated-orcid":false,"given":"Yuchen","family":"Zheng","sequence":"additional","affiliation":[{"name":"College of Information Science and Technology, Shihezi University, Shihezi 832003, China"}]},{"given":"Junyu","family":"Dong","sequence":"additional","affiliation":[{"name":"College of Computer Science and Technology, Ocean University of China, Qingdao 266404, China"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-2952-6642","authenticated-orcid":false,"given":"Guoqiang","family":"Zhong","sequence":"additional","affiliation":[{"name":"College of Computer Science and Technology, Ocean University of China, Qingdao 266404, China"}]}],"member":"1968","published-online":{"date-parts":[[2023,12,4]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","first-page":"263","DOI":"10.1613\/jair.105","article-title":"Solving multiclass learning problems via error-correcting output codes","volume":"2","author":"Dietterich","year":"1995","journal-title":"J. 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