{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2024,9,6]],"date-time":"2024-09-06T06:56:13Z","timestamp":1725605773834},"publisher-location":"Berlin, Heidelberg","reference-count":11,"publisher":"Springer Berlin Heidelberg","isbn-type":[{"type":"print","value":"9783642215568"},{"type":"electronic","value":"9783642215575"}],"license":[{"start":{"date-parts":[[2011,1,1]],"date-time":"2011-01-01T00:00:00Z","timestamp":1293840000000},"content-version":"unspecified","delay-in-days":0,"URL":"http:\/\/www.springer.com\/tdm"}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":[],"published-print":{"date-parts":[[2011]]},"DOI":"10.1007\/978-3-642-21557-5_27","type":"book-chapter","created":{"date-parts":[[2011,9,8]],"date-time":"2011-09-08T15:33:54Z","timestamp":1315496034000},"page":"249-258","source":"Crossref","is-referenced-by-count":0,"title":["Analyzing the Relationship between Diversity and Evidential Fusion Accuracy"],"prefix":"10.1007","author":[{"given":"Yaxin","family":"Bi","sequence":"first","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"297","reference":[{"key":"27_CR1","doi-asserted-by":"publisher","first-page":"1731","DOI":"10.1016\/j.artint.2008.06.002","volume":"17","author":"Y. Bi","year":"2008","unstructured":"Bi, Y., Guan, J., Bell, D.: The combination of multiple classifiers using an evidential approach. Artificial Intelligence\u00a017, 1731\u20131751 (2008)","journal-title":"Artificial Intelligence"},{"key":"27_CR2","series-title":"Communications in Computer and Information Science","doi-asserted-by":"publisher","first-page":"238","DOI":"10.1007\/978-3-642-14055-6_25","volume-title":"Information Processing and Management of Uncertainty in Knowledge-Based Systems. Theory and Methods","author":"Y. Bi","year":"2010","unstructured":"Bi, Y., Wu, S.: Measuring Impact of Diversity of Classifiers on the Accuracy of Evidential Ensemble Classifiers. In: H\u00fcllermeier, E., Kruse, R., Hoffmann, F. (eds.) IPMU 2010. Communications in Computer and Information Science, vol.\u00a080, pp. 238\u2013247. Springer, Heidelberg (2010)"},{"key":"27_CR3","doi-asserted-by":"publisher","first-page":"537","DOI":"10.1177\/014662167900300410","volume":"3","author":"J.L. Fleiss","year":"1979","unstructured":"Fleiss, J.L., Cuzick, J.: The reliability of dichotomous judgments: unequal numbers of judgments per subject. Applied Psychological Measurement\u00a03, 537\u2013542 (1979)","journal-title":"Applied Psychological Measurement"},{"key":"27_CR4","unstructured":"Kohavi, R., Wolpert, D.: Bias plus variance decomposition for zero-one loss functions. In: Proc 13th International Conference of Machine Learning, pp. 275\u2013283 (1996)"},{"key":"27_CR5","doi-asserted-by":"publisher","first-page":"181","DOI":"10.1023\/A:1022859003006","volume":"51","author":"L. Kuncheva","year":"2003","unstructured":"Kuncheva, L., Whitaker, C.J.: Measures of diversity in classifier ensembles and their relationship with the ensemble accuracy. Machine Learning\u00a051, 181\u2013207 (2003)","journal-title":"Machine Learning"},{"key":"27_CR6","doi-asserted-by":"crossref","DOI":"10.1515\/9780691214696","volume-title":"A Mathematical Theory of Evidence","author":"G. Shafer","year":"1976","unstructured":"Shafer, G.: A Mathematical Theory of Evidence, 1st edn. Princeton University Press, Princeton (1976)","edition":"1"},{"key":"27_CR7","unstructured":"Skalak, D.: he sources of increased accuracy for two proposed boosting algorithms. In: Proc. American Association for Artificial Intelligence, AAAI-1996, Integrating Multiple Learned Models Workshop (1996)"},{"issue":"1","key":"27_CR8","doi-asserted-by":"publisher","first-page":"247","DOI":"10.1007\/s10994-006-9449-2","volume":"65","author":"E.K. Tang","year":"2006","unstructured":"E., Tang, E.K., Suganthan, P.N., Yao, X.: An analysis of diversity measures. Machine Learning\u00a065(1), 247\u2013271 (2006)","journal-title":"Machine Learning"},{"key":"27_CR9","volume-title":"Data Mining: Practical machine learning tools and techniques","author":"I.H. Witten","year":"2005","unstructured":"Witten, I.H., Frank, E.: Data Mining: Practical machine learning tools and techniques, 2nd edn. Morgan Kaufmann, San Francisco (2005)","edition":"2"},{"key":"27_CR10","doi-asserted-by":"publisher","first-page":"93","DOI":"10.1016\/0020-0255(87)90007-7","volume":"41","author":"R.R. Yager","year":"1987","unstructured":"Yager, R.R.: On the dempster-shafer framework and new combination rules. Information Science\u00a041, 93\u2013137 (1987)","journal-title":"Information Science"},{"issue":"3","key":"27_CR11","doi-asserted-by":"publisher","first-page":"189","DOI":"10.1016\/0169-023X(95)00038-T","volume":"18","author":"S.S. Anand","year":"1996","unstructured":"Anand, S.S., Bell, D., Hughes, J.G.: EDM: A General Framework for Data Mining Based on Evidence Theory. Data Knowl. Eng\u00a018(3), 189\u2013223 (1996)","journal-title":"Data Knowl. Eng"}],"container-title":["Lecture Notes in Computer Science","Multiple Classifier Systems"],"original-title":[],"link":[{"URL":"http:\/\/link.springer.com\/content\/pdf\/10.1007\/978-3-642-21557-5_27","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2021,12,3]],"date-time":"2021-12-03T22:55:48Z","timestamp":1638572148000},"score":1,"resource":{"primary":{"URL":"http:\/\/link.springer.com\/10.1007\/978-3-642-21557-5_27"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2011]]},"ISBN":["9783642215568","9783642215575"],"references-count":11,"URL":"https:\/\/doi.org\/10.1007\/978-3-642-21557-5_27","relation":{},"ISSN":["0302-9743","1611-3349"],"issn-type":[{"type":"print","value":"0302-9743"},{"type":"electronic","value":"1611-3349"}],"subject":[],"published":{"date-parts":[[2011]]}}}