{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,7,27]],"date-time":"2026-07-27T23:21:36Z","timestamp":1785194496216,"version":"3.55.0"},"publisher-location":"Cham","reference-count":20,"publisher":"Springer International Publishing","isbn-type":[{"value":"9783030889418","type":"print"},{"value":"9783030889425","type":"electronic"}],"license":[{"start":{"date-parts":[[2021,1,1]],"date-time":"2021-01-01T00:00:00Z","timestamp":1609459200000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/www.springer.com\/tdm"},{"start":{"date-parts":[[2021,1,1]],"date-time":"2021-01-01T00:00:00Z","timestamp":1609459200000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/www.springer.com\/tdm"}],"content-domain":{"domain":["link.springer.com"],"crossmark-restriction":false},"short-container-title":[],"published-print":{"date-parts":[[2021]]},"DOI":"10.1007\/978-3-030-88942-5_7","type":"book-chapter","created":{"date-parts":[[2021,10,9]],"date-time":"2021-10-09T05:14:15Z","timestamp":1633756455000},"page":"78-93","update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":1,"title":["Combining Predictions Under Uncertainty: The Case of Random Decision Trees"],"prefix":"10.1007","author":[{"given":"Florian","family":"Busch","sequence":"first","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Moritz","family":"Kulessa","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Eneldo","family":"Loza Menc\u00eda","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Hendrik","family":"Blockeel","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"297","published-online":{"date-parts":[[2021,10,9]]},"reference":[{"key":"7_CR1","doi-asserted-by":"crossref","unstructured":"Bostrom, H.: Estimating class probabilities in random forests. In: 6th International Conference on Machine Learning and Applications, pp. 211\u2013216 (2007)","DOI":"10.1109\/ICMLA.2007.64"},{"issue":"1","key":"7_CR2","doi-asserted-by":"publisher","first-page":"5","DOI":"10.1023\/A:1010933404324","volume":"45","author":"L Breiman","year":"2001","unstructured":"Breiman, L.: Random forests. Mach. Learn. 45(1), 5\u201332 (2001)","journal-title":"Mach. Learn."},{"key":"7_CR3","doi-asserted-by":"crossref","unstructured":"Costa, V.S., Farias, A.D.S., Bedregal, B., Santiago, R.H., de P. Canuto, A.M.: Combining multiple algorithms in classifier ensembles using generalized mixture functions. Neurocomputing 313, 402\u2013414 (2018)","DOI":"10.1016\/j.neucom.2018.06.021"},{"key":"7_CR4","doi-asserted-by":"crossref","unstructured":"Den\u0153ux, T.: The cautious rule of combination for belief functions and some extensions. In: 9th International Conference on Information Fusion, pp. 1\u20138 (2006)","DOI":"10.1109\/ICIF.2006.301572"},{"key":"7_CR5","series-title":"Lecture Notes in Computer Science","doi-asserted-by":"publisher","first-page":"1","DOI":"10.1007\/3-540-45014-9_1","volume-title":"Multiple Classifier Systems","author":"TG Dietterich","year":"2000","unstructured":"Dietterich, T.G.: Ensemble methods in machine learning. In: Kittler, J., Roli, F. (eds.) MCS 2000. LNCS, vol. 1857, pp. 1\u201315. Springer, Heidelberg (2000). https:\/\/doi.org\/10.1007\/3-540-45014-9_1"},{"key":"7_CR6","unstructured":"Fan, W., Wang, H., Yu, P.S., Ma, S.: Is random model better? On its accuracy and efficiency. In: 3rd IEEE International Conference on Data Mining (2003)"},{"key":"7_CR7","doi-asserted-by":"crossref","unstructured":"Farias, A.D.S., Santiago, R.H.N., Bedregal, B.: Some properties of generalized mixture functions. In: IEEE International Conference on Fuzzy Systems, pp. 288\u2013293 (2016)","DOI":"10.1109\/FUZZ-IEEE.2016.7737699"},{"key":"7_CR8","series-title":"Lecture Notes in Computer Science (Lecture Notes in Artificial Intelligence)","doi-asserted-by":"publisher","first-page":"33","DOI":"10.1007\/978-3-030-01771-2_3","volume-title":"Discovery Science","author":"M Kulessa","year":"2018","unstructured":"Kulessa, M., Loza Menc\u00eda, E.: Dynamic classifier chain with random decision trees. In: Soldatova, L., Vanschoren, J., Papadopoulos, G., Ceci, M. (eds.) DS 2018. LNCS (LNAI), vol. 11198, pp. 33\u201350. Springer, Cham (2018). https:\/\/doi.org\/10.1007\/978-3-030-01771-2_3"},{"issue":"2","key":"7_CR9","doi-asserted-by":"publisher","first-page":"75","DOI":"10.1007\/BF00117809","volume":"6","author":"Y Lu","year":"1996","unstructured":"Lu, Y.: Knowledge integration in a multiple classifier system. Appl. Intell. 6(2), 75\u201386 (1996)","journal-title":"Appl. Intell."},{"issue":"6","key":"7_CR10","doi-asserted-by":"publisher","first-page":"2168","DOI":"10.1109\/TCYB.2018.2821679","volume":"49","author":"TT Nguyen","year":"2018","unstructured":"Nguyen, T.T., Pham, X.C., Liew, A.W.C., Pedrycz, W.: Aggregation of classifiers: a justifiable information granularity approach. IEEE Trans. Cybern. 49(6), 2168\u20132177 (2018)","journal-title":"IEEE Trans. Cybern."},{"key":"7_CR11","doi-asserted-by":"crossref","unstructured":"Nguyen, V.L., Destercke, S., Masson, M.H., H\u00fcllermeier, E.: Reliable multi-class classification based on pairwise epistemic and aleatoric uncertainty. In: International Joint Conference on Artificial Intelligence, pp. 5089\u20135095 (2018)","DOI":"10.24963\/ijcai.2018\/706"},{"issue":"3","key":"7_CR12","doi-asserted-by":"publisher","first-page":"199","DOI":"10.1023\/A:1024099825458","volume":"52","author":"F Provost","year":"2003","unstructured":"Provost, F., Domingos, P.: Tree induction for probability-based ranking. Mach. Learn. 52(3), 199\u2013215 (2003)","journal-title":"Mach. Learn."},{"key":"7_CR13","doi-asserted-by":"crossref","unstructured":"Raza, M., Gondal, I., Green, D., Coppel, R.L.: Classifier fusion using dempster-shafer theory of evidence to predict breast cancer tumors. In: IEEE Region 10 International Conference TENCON, pp. 1\u20134 (2006)","DOI":"10.1109\/TENCON.2006.343718"},{"key":"7_CR14","first-page":"1","volume":"7","author":"D Ruta","year":"2000","unstructured":"Ruta, D., Gabrys, B.: An overview of classifier fusion methods. Comput. Inf. Syst. 7, 1\u201310 (2000)","journal-title":"Comput. Inf. Syst."},{"key":"7_CR15","doi-asserted-by":"crossref","unstructured":"Shafer, G.: A Mathematical Theory of Evidence, vol. 42. Princeton University Press (1976)","DOI":"10.1515\/9780691214696"},{"key":"7_CR16","series-title":"Lecture Notes in Computer Science","doi-asserted-by":"publisher","first-page":"444","DOI":"10.1007\/978-3-030-44584-3_35","volume-title":"Advances in Intelligent Data Analysis XVIII","author":"MH Shaker","year":"2020","unstructured":"Shaker, M.H., H\u00fcllermeier, E.: Aleatoric and epistemic uncertainty with random forests. In: Berthold, M.R., Feelders, A., Krempl, G. (eds.) IDA 2020. LNCS, vol. 12080, pp. 444\u2013456. Springer, Cham (2020). https:\/\/doi.org\/10.1007\/978-3-030-44584-3_35"},{"issue":"1","key":"7_CR17","doi-asserted-by":"publisher","first-page":"1","DOI":"10.1016\/0888-613X(93)90005-X","volume":"9","author":"P Smets","year":"1993","unstructured":"Smets, P.: Belief functions: the disjunctive rule of combination and the generalized Bayesian theorem. Int. J. Approximate Reasoning 9(1), 1\u201335 (1993)","journal-title":"Int. J. Approximate Reasoning"},{"issue":"2","key":"7_CR18","doi-asserted-by":"publisher","first-page":"241","DOI":"10.1016\/S0893-6080(05)80023-1","volume":"5","author":"D Wolpert","year":"1992","unstructured":"Wolpert, D.: Stacked generalization. Neural Netw. 5(2), 241\u2013259 (1992)","journal-title":"Neural Netw."},{"issue":"8","key":"7_CR19","doi-asserted-by":"publisher","first-page":"1177","DOI":"10.1109\/TNNLS.2012.2200299","volume":"23","author":"SE Yuksel","year":"2012","unstructured":"Yuksel, S.E., Wilson, J.N., Gader, P.D.: Twenty years of mixture of experts. IEEE Trans. Neural Netw. Learn. Syst. 23(8), 1177\u20131193 (2012)","journal-title":"IEEE Trans. Neural Netw. Learn. Syst."},{"key":"7_CR20","doi-asserted-by":"crossref","unstructured":"Zhou, S., Mentch, L.: Trees, forests, chickens, and eggs: when and why to prune trees in a random forest. arXiv preprint arXiv:2103.16700 (2021)","DOI":"10.1002\/sam.11594"}],"container-title":["Lecture Notes in Computer Science","Discovery Science"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/978-3-030-88942-5_7","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2023,1,11]],"date-time":"2023-01-11T13:31:39Z","timestamp":1673443899000},"score":1,"resource":{"primary":{"URL":"https:\/\/link.springer.com\/10.1007\/978-3-030-88942-5_7"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2021]]},"ISBN":["9783030889418","9783030889425"],"references-count":20,"URL":"https:\/\/doi.org\/10.1007\/978-3-030-88942-5_7","relation":{},"ISSN":["0302-9743","1611-3349"],"issn-type":[{"value":"0302-9743","type":"print"},{"value":"1611-3349","type":"electronic"}],"subject":[],"published":{"date-parts":[[2021]]},"assertion":[{"value":"9 October 2021","order":1,"name":"first_online","label":"First Online","group":{"name":"ChapterHistory","label":"Chapter History"}},{"value":"DS","order":1,"name":"conference_acronym","label":"Conference Acronym","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"International Conference on Discovery Science","order":2,"name":"conference_name","label":"Conference Name","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"Halifax, NS","order":3,"name":"conference_city","label":"Conference City","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"Canada","order":4,"name":"conference_country","label":"Conference Country","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"2021","order":5,"name":"conference_year","label":"Conference Year","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"11 October 2021","order":7,"name":"conference_start_date","label":"Conference Start Date","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"13 October 2021","order":8,"name":"conference_end_date","label":"Conference End Date","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"24","order":9,"name":"conference_number","label":"Conference Number","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"dis2021","order":10,"name":"conference_id","label":"Conference ID","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"https:\/\/ds2021.cs.dal.ca\/","order":11,"name":"conference_url","label":"Conference URL","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"Single-blind","order":1,"name":"type","label":"Type","group":{"name":"ConfEventPeerReviewInformation","label":"Peer Review Information (provided by the conference organizers)"}},{"value":"EasyChair","order":2,"name":"conference_management_system","label":"Conference Management System","group":{"name":"ConfEventPeerReviewInformation","label":"Peer Review Information (provided by the conference organizers)"}},{"value":"76","order":3,"name":"number_of_submissions_sent_for_review","label":"Number of Submissions Sent for Review","group":{"name":"ConfEventPeerReviewInformation","label":"Peer Review Information (provided by the conference organizers)"}},{"value":"15","order":4,"name":"number_of_full_papers_accepted","label":"Number of Full Papers Accepted","group":{"name":"ConfEventPeerReviewInformation","label":"Peer Review Information (provided by the conference organizers)"}},{"value":"21","order":5,"name":"number_of_short_papers_accepted","label":"Number of Short Papers Accepted","group":{"name":"ConfEventPeerReviewInformation","label":"Peer Review Information (provided by the conference organizers)"}},{"value":"20% - The value is computed by the equation \"Number of Full Papers Accepted \/ Number of Submissions Sent for Review * 100\" and then rounded to a whole number.","order":6,"name":"acceptance_rate_of_full_papers","label":"Acceptance Rate of Full Papers","group":{"name":"ConfEventPeerReviewInformation","label":"Peer Review Information (provided by the conference organizers)"}},{"value":"2.8","order":7,"name":"average_number_of_reviews_per_paper","label":"Average Number of Reviews per Paper","group":{"name":"ConfEventPeerReviewInformation","label":"Peer Review Information (provided by the conference organizers)"}},{"value":"3.9","order":8,"name":"average_number_of_papers_per_reviewer","label":"Average Number of Papers per Reviewer","group":{"name":"ConfEventPeerReviewInformation","label":"Peer Review Information (provided by the conference organizers)"}},{"value":"Yes","order":9,"name":"external_reviewers_involved","label":"External Reviewers Involved","group":{"name":"ConfEventPeerReviewInformation","label":"Peer Review Information (provided by the conference organizers)"}},{"value":"Due to the COVID-19 pandemic, the conference took place online.","order":10,"name":"additional_info_on_review_process","label":"Additional Info on Review Process","group":{"name":"ConfEventPeerReviewInformation","label":"Peer Review Information (provided by the conference organizers)"}}]}}