{"action":"opened","issue":{"url":"https://api.github.com/repos/ivypublisher/Scientific-Journal-of-Information-Engineering/issues/70","labels_url":"https://api.github.com/repos/ivypublisher/Scientific-Journal-of-Information-Engineering/issues/70/labels{/name}","comments_url":"https://api.github.com/repos/ivypublisher/Scientific-Journal-of-Information-Engineering/issues/70/comments","events_url":"https://api.github.com/repos/ivypublisher/Scientific-Journal-of-Information-Engineering/issues/70/events","html_url":"https://github.com/ivypublisher/Scientific-Journal-of-Information-Engineering/issues/70","id":84878017,"number":70,"title":"A Neural Network Selection Approach of Constructing Ensemble Based on CS Algorithm","user":{"login":"ivypublisher","id":6970392,"avatar_url":"https://avatars.githubusercontent.com/u/6970392?v=3","gravatar_id":"","url":"https://api.github.com/users/ivypublisher","html_url":"https://github.com/ivypublisher","followers_url":"https://api.github.com/users/ivypublisher/followers","following_url":"https://api.github.com/users/ivypublisher/following{/other_user}","gists_url":"https://api.github.com/users/ivypublisher/gists{/gist_id}","starred_url":"https://api.github.com/users/ivypublisher/starred{/owner}{/repo}","subscriptions_url":"https://api.github.com/users/ivypublisher/subscriptions","organizations_url":"https://api.github.com/users/ivypublisher/orgs","repos_url":"https://api.github.com/users/ivypublisher/repos","events_url":"https://api.github.com/users/ivypublisher/events{/privacy}","received_events_url":"https://api.github.com/users/ivypublisher/received_events","type":"User","site_admin":false},"labels":[],"state":"open","locked":false,"assignee":null,"milestone":null,"comments":0,"created_at":"2015-06-04T02:52:16Z","updated_at":"2015-06-04T02:52:16Z","closed_at":null,"body":"Author: Jun Hua, Tiecheng Song, Yu Jiang, Jing Hu, Shidong Liu, Jinghong Guo\r\nAbstract: Selective neural network ensemble is at present a heated research issue in the field of neural network, aimed at improving classification results accompanied by boosting generalization ability. Based on existing techniques, a neural network selection algorithm of constructing ensemble named CSEN is presented, which, to some extent, tackles the problem of selecting component neural networks. Experiments were conducted to test the validity of CSEN on several datasets and results show strong stability and high running efficiency of the algorithm. Moreover, its misclassification rate turns out to be relatively lower compared with its counterparts and leads to a much better performance.\r\nKeywords: Neural Network, Cuckoo Search Algorithm, Selective Ensemble\r\n\r\nhttp://www.sjie.org/paperinfo/21439.shtml"}}