{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2024,4,5]],"date-time":"2024-04-05T08:35:12Z","timestamp":1712306112516},"reference-count":27,"publisher":"International Academy Publishing (IAP)","issue":"7","content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["JCP"],"DOI":"10.4304\/jcp.9.7.1547-1552","type":"journal-article","created":{"date-parts":[[2014,6,23]],"date-time":"2014-06-23T23:49:27Z","timestamp":1403567367000},"source":"Crossref","is-referenced-by-count":2,"title":["On Adjustment Functions for Weight-Adjusted Voting-Based Ensembles of Classifiers"],"prefix":"10.17706","volume":"9","author":[{"given":"Kuo-Wei","family":"Hsu","sequence":"first","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"7163","published-online":{"date-parts":[[2014,7,1]]},"reference":[{"key":"ref1","doi-asserted-by":"crossref","first-page":"169","DOI":"10.1613\/jair.614","article-title":"Popular Ensemble Methods: An Empirical Study","volume":"11","author":"Opitz","year":"1999","unstructured":"[1] D. Opitz and R. Maclin, \"Popular Ensemble Methods: An Empirical Study,\" Journal of Artificial Intelligence Research, vol. 11, pp. 169-198, 1999.","journal-title":"J Artif Intell Res","ISSN":"http:\/\/id.crossref.org\/issn\/1076-9757","issn-type":"print"},{"key":"ref2","doi-asserted-by":"publisher","DOI":"10.1007\/3-540-45014-9_1"},{"key":"ref3","doi-asserted-by":"publisher","DOI":"10.1007\/s10462-009-9124-7"},{"key":"ref4","doi-asserted-by":"publisher","DOI":"10.1007\/BF00058655"},{"key":"ref5","doi-asserted-by":"publisher","DOI":"10.1214\/aos\/1031689014"},{"key":"ref6","doi-asserted-by":"publisher","DOI":"10.1023\/A:1007515423169"},{"key":"ref7","doi-asserted-by":"publisher","DOI":"10.1007\/3-540-45869-7_21"},{"key":"ref8","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-642-21557-5_37"},{"key":"ref9","article-title":"A taxonomy and short review of ensemble selection","volume-title":"Workshop on Supervised and Unsupervised Ensemble Methods and Their Applications","author":"Tsoumakas","year":"2008","unstructured":"[9] G. Tsoumakas, I. Partalas, and I. Vlahavas, \"A taxonomy and short review of ensemble selection,\" in Workshop on Supervised and Unsupervised Ensemble Methods and Their Applications, 2008."},{"key":"ref10","doi-asserted-by":"publisher","DOI":"10.1016\/j.inffus.2007.07.002"},{"key":"ref11","first-page":"1","article-title":"A weighted voting framework for classifiers ensembles","author":"Kuncheva","year":"2012","unstructured":"[11] L. I. Kuncheva and J. J. Rodriguez,\" A weighted voting framework for classifiers ensembles,\" Knowledge and Information Systems, pp. 1-17, 2012.","journal-title":"Knowl Inf Syst","ISSN":"http:\/\/id.crossref.org\/issn\/0219-1377","issn-type":"print"},{"key":"ref12","doi-asserted-by":"publisher","DOI":"10.1016\/j.jkss.2011.03.002"},{"key":"ref13","first-page":"1935","article-title":"Ensemble Techniques with Weighted Combination Rules for Early Diagnosis of Alzheimer's Disease","volume-title":"Proceedings of International Joint Conference on Neural Networks","author":"Stepenosky","year":"2006","unstructured":"[13] N. Stepenosky, J. Kounios, C. Clark, and R. Polikar, \"Ensemble Techniques with Weighted Combination Rules for Early Diagnosis of Alzheimer's Disease,\" in Proceedings of International Joint Conference on Neural Networks, pp. 1935-1942, 2006."},{"key":"ref14","doi-asserted-by":"publisher","DOI":"10.1007\/s10489-012-0388-2"},{"key":"ref15","doi-asserted-by":"publisher","DOI":"10.1006\/inco.1994.1009"},{"key":"ref16","first-page":"465","article-title":"Effective Voting of Heterogeneous Classifiers","volume-title":"Proceedings of European Conference on Machine Learning","author":"Tsoumakas","year":"2004","unstructured":"[16] G. Tsoumakas, I. Katakis, and I. Vlahavas, \"Effective Voting of Heterogeneous Classifiers,\" in Proceedings of European Conference on Machine Learning, pp. 465-476, 2004."},{"key":"ref17","doi-asserted-by":"publisher","DOI":"10.1007\/11815921_77"},{"key":"ref18","doi-asserted-by":"publisher","DOI":"10.1007\/11739685_91"},{"key":"ref19","first-page":"323","article-title":"Optimizing Weights by Genetic Algorithm for Neural Network Ensemble","volume-title":"Proceedings of International Symposium on Neural Networks","author":"Shen","year":"2004","unstructured":"[19] Z.-Q. Shen and F.-S. Kong, \"Optimizing Weights by Genetic Algorithm for Neural Network Ensemble,\" in Proceedings of International Symposium on Neural Networks, pp. 323-331, 2004."},{"key":"ref20","doi-asserted-by":"crossref","DOI":"10.1109\/ICNC.2007.207","article-title":"An improved bagging neural network ensemble algorithm and its application","volume-title":"International Conference on Natural Computation","author":"Chen","year":"2007","unstructured":"[20] R. Chen and J. Yu, \"An improved bagging neural network ensemble algorithm and its application,\" in International Conference on Natural Computation, 2007."},{"key":"ref21","first-page":"1131","article-title":"Dynamically weighted majority voting for incremental learning and comparison of three boosting based approaches","volume-title":"Proceedings of International Joint Conference on Neural Networks","author":"Gangardiwala","year":"2005","unstructured":"[22] A. Gangardiwala and R. Polikar, \"Dynamically weighted majority voting for incremental learning and comparison of three boosting based approaches,\" in Proceedings of International Joint Conference on Neural Networks, pp. 1131-1136, 2005."},{"key":"ref22","doi-asserted-by":"publisher","DOI":"10.1145\/1656274.1656278"},{"key":"ref23","volume-title":"C4 5","author":"Quinlan","year":"1993","unstructured":"[26] R. Quinlan, C4.5: Programs for Machine Learning, Morgan Kaufmann Publishers, San Mateo, CA, 1993."},{"key":"ref24","doi-asserted-by":"publisher","DOI":"10.1023\/A:1007607513941"},{"issue":"no. 2","key":"ref25","first-page":"121","article-title":"A Bagging Method using Decision Trees in the Role of Base Classifiers","volume":"3","author":"Machova","year":"2006","unstructured":"[28] K. Machova, F. Barcak, and P. Bednar, \"A Bagging Method using Decision Trees in the Role of Base Classifiers,\" Acta Polytechnica Hungarica, vol. 3, no. 2, pp. 121-132, 2006.","journal-title":"Acta Polytechnica Hungarica"},{"key":"ref26","doi-asserted-by":"publisher","DOI":"10.3923\/ajit.2010.300.306"},{"issue":"no. 5","key":"ref27","first-page":"560","article-title":"Weight-adjusted bagging of classification algorithms sensitive to missing values","volume":"3","author":"Hsu","year":"2013","unstructured":"[30] K.-W. Hsu, \"Weight-adjusted bagging of classification algorithms sensitive to missing values,\" International Journal of Information and Education Technology, vol. 3, no. 5, pp. 560-566, 2013.","journal-title":"International Journal of Information and Education Technology"}],"container-title":["Journal of Computers"],"original-title":[],"deposited":{"date-parts":[[2019,8,11]],"date-time":"2019-08-11T21:08:12Z","timestamp":1565557692000},"score":1,"resource":{"primary":{"URL":"http:\/\/ojs.academypublisher.com\/index.php\/jcp\/article\/view\/12866"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2014,7,1]]},"references-count":27,"journal-issue":{"issue":"7","published-online":{"date-parts":[[2014,7,1]]}},"URL":"https:\/\/doi.org\/10.4304\/jcp.9.7.1547-1552","relation":{},"ISSN":["1796-203X"],"issn-type":[{"value":"1796-203X","type":"print"}],"subject":[],"published":{"date-parts":[[2014,7,1]]}}}