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It is shown that a single DBN classifier is better than support vector machine and logistic regression algorithm. The model established by the integrated deep confidence network has a significant improvement in classification accuracy compared to a single DBN classifier, and solves the unstable classification effect of a single DBN classifier.<\/jats:p>","DOI":"10.3233\/jcm-204654","type":"journal-article","created":{"date-parts":[[2020,10,2]],"date-time":"2020-10-02T13:58:43Z","timestamp":1601647123000},"page":"817-828","source":"Crossref","is-referenced-by-count":2,"title":["Diabetes prediction model based on deep belief network"],"prefix":"10.66113","volume":"21","author":[{"given":"Li-Ying","family":"Lang","sequence":"first","affiliation":[{"name":"Hebei University of Engineering, Handan, Hebei 056038, China"},{"name":"Hebei University of Technology, Tianjin 300401, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Zheng","family":"Gao","sequence":"additional","affiliation":[{"name":"School of Information and Electrical Engineering, Hebei University of Engineering, Handan, 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