{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,3,27]],"date-time":"2025-03-27T02:11:28Z","timestamp":1743041488259,"version":"3.40.3"},"publisher-location":"Cham","reference-count":22,"publisher":"Springer International Publishing","isbn-type":[{"type":"print","value":"9783030501426"},{"type":"electronic","value":"9783030501433"}],"license":[{"start":{"date-parts":[[2020,1,1]],"date-time":"2020-01-01T00:00:00Z","timestamp":1577836800000},"content-version":"tdm","delay-in-days":0,"URL":"http:\/\/www.springer.com\/tdm"},{"start":{"date-parts":[[2020,1,1]],"date-time":"2020-01-01T00:00:00Z","timestamp":1577836800000},"content-version":"vor","delay-in-days":0,"URL":"http:\/\/www.springer.com\/tdm"}],"content-domain":{"domain":["link.springer.com"],"crossmark-restriction":false},"short-container-title":[],"published-print":{"date-parts":[[2020]]},"DOI":"10.1007\/978-3-030-50143-3_7","type":"book-chapter","created":{"date-parts":[[2020,6,5]],"date-time":"2020-06-05T21:03:01Z","timestamp":1591390981000},"page":"82-95","update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":0,"title":["Binary Credal Classification Under Sparsity Constraints"],"prefix":"10.1007","author":[{"ORCID":"https:\/\/orcid.org\/0000-0002-6851-154X","authenticated-orcid":false,"given":"Tathagata","family":"Basu","sequence":"first","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-1294-600X","authenticated-orcid":false,"given":"Matthias C. M.","family":"Troffaes","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-9457-2020","authenticated-orcid":false,"given":"Jochen","family":"Einbeck","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"297","published-online":{"date-parts":[[2020,6,5]]},"reference":[{"key":"7_CR1","unstructured":"Agresti, A.: Categorical Data Analysis. Wiley Series in Probability and Statistics. Wiley, Hoboken (2013). https:\/\/books.google.co.uk\/books?id=UOrr47-2oisC"},{"issue":"23","key":"7_CR2","doi-asserted-by":"publisher","first-page":"9326","DOI":"10.1016\/j.eswa.2015.08.016","volume":"42","author":"ZY Algamal","year":"2015","unstructured":"Algamal, Z.Y., Lee, M.H.: Penalized logistic regression with the adaptive lasso for gene selection in high-dimensional cancer classification. Expert Syst. Appl. 42(23), 9326\u20139332 (2015). https:\/\/doi.org\/10.1016\/j.eswa.2015.08.016","journal-title":"Expert Syst. Appl."},{"issue":"1","key":"7_CR3","doi-asserted-by":"publisher","first-page":"183","DOI":"10.1080\/15598608.2009.10411919","volume":"3","author":"M Bickis","year":"2009","unstructured":"Bickis, M.: The imprecise logit-normal model and its application to estimating hazard functions. J. Stat. Theory Pract. 3(1), 183\u2013195 (2009). https:\/\/doi.org\/10.1080\/15598608.2009.10411919","journal-title":"J. Stat. Theory Pract."},{"key":"7_CR4","doi-asserted-by":"publisher","first-page":"818","DOI":"10.1016\/j.csda.2012.11.010","volume":"71","author":"G Corani","year":"2014","unstructured":"Corani, G., Antonucci, A.: Credal ensembles of classifiers. Comput. Stat. Data Anal. 71, 818\u2013831 (2014). https:\/\/doi.org\/10.1016\/j.csda.2012.11.010","journal-title":"Comput. Stat. Data Anal."},{"issue":"9","key":"7_CR5","doi-asserted-by":"publisher","first-page":"1053","DOI":"10.1016\/j.ijar.2010.08.007","volume":"51","author":"G Corani","year":"2010","unstructured":"Corani, G., de Campos, C.P.: A tree augmented classifier based on extreme imprecise Dirichlet model. Int. J. Approx. Reason. 51(9), 1053\u20131068 (2010). https:\/\/doi.org\/10.1016\/j.ijar.2010.08.007","journal-title":"Int. J. Approx. Reason."},{"key":"7_CR6","first-page":"581","volume":"9","author":"G Corani","year":"2008","unstructured":"Corani, G., Zaffalon, M.: Learning reliable classifiers from small or incomplete data sets: the naive credal classifier 2. J. Mach. Learn. Res. 9, 581\u2013621 (2008)","journal-title":"J. Mach. Learn. Res."},{"key":"7_CR7","unstructured":"Jos\u00e9 del Coz, J., D\u00edez, J., Bahamonde, A.: Learning nondeterministic classifiers. J. Mach. Learn. Res. 10, 2273\u20132293 (2009)"},{"issue":"456","key":"7_CR8","doi-asserted-by":"publisher","first-page":"1348","DOI":"10.1198\/016214501753382273","volume":"96","author":"J Fan","year":"2001","unstructured":"Fan, J., Li, R.: Variable selection via nonconcave penalized likelihood and its oracle properties. J. Am. Stat. Assoc. 96(456), 1348\u20131360 (2001). http:\/\/www.jstor.org\/stable\/3085904","journal-title":"J. Am. Stat. Assoc."},{"issue":"1","key":"7_CR9","doi-asserted-by":"publisher","first-page":"1","DOI":"10.18637\/jss.v033.i01","volume":"33","author":"J Friedman","year":"2010","unstructured":"Friedman, J., Hastie, T., Tibshirani, R.: Regularization paths for generalized linear models via coordinate descent. J. Stat. Softw. 33(1), 1\u201322 (2010). http:\/\/www.jstatsoft.org\/v33\/i01\/","journal-title":"J. Stat. Softw."},{"issue":"1","key":"7_CR10","doi-asserted-by":"publisher","first-page":"75","DOI":"10.1016\/0893-6080(88)90023-8","volume":"1","author":"RP Gorman","year":"1988","unstructured":"Gorman, R.P., Sejnowski, T.J.: Analysis of hidden units in a layered network trained to classify sonar targets. Neural Netw. 1(1), 75\u201389 (1988). https:\/\/doi.org\/10.1016\/0893-6080(88)90023-8","journal-title":"Neural Netw."},{"issue":"3","key":"7_CR11","doi-asserted-by":"publisher","first-page":"404","DOI":"10.1145\/321075.321084","volume":"8","author":"ME Maron","year":"1961","unstructured":"Maron, M.E.: Automatic indexing: an experimental inquiry. J. ACM 8(3), 404\u2013417 (1961). https:\/\/doi.org\/10.1145\/321075.321084","journal-title":"J. ACM"},{"key":"7_CR12","doi-asserted-by":"publisher","DOI":"10.1007\/978-1-4419-8853-9","volume-title":"Introductory Lectures on Convex Optimization: A Basic Course","author":"Y Nesterov","year":"2014","unstructured":"Nesterov, Y.: Introductory Lectures on Convex Optimization: A Basic Course, 1st edn. Springer, Heidelberg (2014). https:\/\/doi.org\/10.1007\/978-1-4419-8853-9","edition":"1"},{"key":"7_CR13","series-title":"Communications in Computer and Information Science","doi-asserted-by":"publisher","first-page":"476","DOI":"10.1007\/978-3-319-08852-5_49","volume-title":"Information Processing and Management of Uncertainty in Knowledge-Based Systems","author":"L Paton","year":"2014","unstructured":"Paton, L., Troffaes, M.C.M., Boatman, N., Hussein, M., Hart, A.: Multinomial logistic regression on Markov chains for crop rotation modelling. In: Laurent, A., Strauss, O., Bouchon-Meunier, B., Yager, R.R. (eds.) IPMU 2014. CCIS, vol. 444, pp. 476\u2013485. Springer, Cham (2014). https:\/\/doi.org\/10.1007\/978-3-319-08852-5_49"},{"key":"7_CR14","unstructured":"Paton, L., Troffaes, M.C.M., Boatman, N., Hussein, M., Hart, A.: A robust Bayesian analysis of the impact of policy decisions on crop rotations. In: Augustin, T., Doria, S., Miranda, E., Quaeghebeur, E. (eds.) ISIPTA 2015: Proceedings of the 9th International Symposium on Imprecise Probability: Theories and Applications, Pescara, Italy, 20\u201324 July 2015, pp. 217\u2013226. SIPTA, July 2015. http:\/\/dro.dur.ac.uk\/15736\/"},{"issue":"17","key":"7_CR15","doi-asserted-by":"publisher","first-page":"2246","DOI":"10.1093\/bioinformatics\/btg308","volume":"19","author":"S Shevade","year":"2003","unstructured":"Shevade, S., Keerthi, S.: A simple and efficient algorithm for gene selection using sparse logistic regression. Bioinformatics 19(17), 2246\u20132253 (2003). https:\/\/doi.org\/10.1093\/bioinformatics\/btg308","journal-title":"Bioinformatics"},{"issue":"1","key":"7_CR16","doi-asserted-by":"crossref","first-page":"267","DOI":"10.1111\/j.2517-6161.1996.tb02080.x","volume":"58","author":"R Tibshirani","year":"1996","unstructured":"Tibshirani, R.: Regression shrinkage and selection via the lasso. J. R. Stat. Soc.: Ser. B (Stat. Methodol.) 58(1), 267\u2013288 (1996). http:\/\/www.jstor.org\/stable\/2346178","journal-title":"J. R. Stat. Soc.: Ser. B (Stat. Methodol.)"},{"issue":"1","key":"7_CR17","doi-asserted-by":"publisher","first-page":"181","DOI":"10.1109\/TNSRE.2013.2293575","volume":"22","author":"A Tsanas","year":"2014","unstructured":"Tsanas, A., Little, M.A., Fox, C., Ramig, L.O.: Objective automatic assessment of rehabilitative speech treatment in Parkinson\u2019s disease. IEEE Trans. Neural Syst. Rehabil. Eng. 22(1), 181\u2013190 (2014)","journal-title":"IEEE Trans. Neural Syst. Rehabil. Eng."},{"key":"7_CR18","doi-asserted-by":"crossref","unstructured":"Walley, P.: Statistical Reasoning with Imprecise Probabilities. Monographs on Statistics & Applied Probability. Chapman & Hall\/CRC , Taylor & Francis, New York (1991). https:\/\/books.google.co.uk\/books?id=-hbvAAAAMAAJ","DOI":"10.1007\/978-1-4899-3472-7"},{"key":"7_CR19","doi-asserted-by":"publisher","unstructured":"Zaffalon, M.: The Naive credal classifier. J. Stat. Plann. Infer. 105(1), 5\u201321 (2002). https:\/\/doi.org\/10.1016\/S0378-3758(01)00201-4 . Imprecise Probability Models and their Applications","DOI":"10.1016\/S0378-3758(01)00201-4"},{"key":"7_CR20","doi-asserted-by":"publisher","unstructured":"Zaffalon, M., Corani, G., Mau\u00e1, D.: Evaluating credal classifiers by utility-discounted predictive accuracy. Int. J. Approx. Reason. 53(8), 1282\u20131301 (2012). https:\/\/doi.org\/10.1016\/j.ijar.2012.06.022 . Imprecise Probability: Theories and Applications (ISIPTA 2011)","DOI":"10.1016\/j.ijar.2012.06.022"},{"issue":"3","key":"7_CR21","doi-asserted-by":"publisher","first-page":"427","DOI":"10.1093\/biostatistics\/kxg046","volume":"5","author":"J Zhu","year":"2004","unstructured":"Zhu, J., Hastie, T.: Classification of gene microarrays by penalized logistic regression. Biostatistics 5(3), 427\u2013443 (2004). https:\/\/doi.org\/10.1093\/biostatistics\/kxg046","journal-title":"Biostatistics"},{"issue":"476","key":"7_CR22","doi-asserted-by":"publisher","first-page":"1418","DOI":"10.1198\/016214506000000735","volume":"101","author":"H Zou","year":"2006","unstructured":"Zou, H.: The adaptive lasso and its oracle properties. J. Am. Stat. Assoc. 101(476), 1418\u20131429 (2006). https:\/\/doi.org\/10.1198\/016214506000000735","journal-title":"J. Am. Stat. Assoc."}],"container-title":["Communications in Computer and Information Science","Information Processing and Management of Uncertainty in Knowledge-Based Systems"],"original-title":[],"language":"en","link":[{"URL":"http:\/\/link.springer.com\/content\/pdf\/10.1007\/978-3-030-50143-3_7","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2024,8,7]],"date-time":"2024-08-07T01:26:08Z","timestamp":1722993968000},"score":1,"resource":{"primary":{"URL":"http:\/\/link.springer.com\/10.1007\/978-3-030-50143-3_7"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2020]]},"ISBN":["9783030501426","9783030501433"],"references-count":22,"URL":"https:\/\/doi.org\/10.1007\/978-3-030-50143-3_7","relation":{},"ISSN":["1865-0929","1865-0937"],"issn-type":[{"type":"print","value":"1865-0929"},{"type":"electronic","value":"1865-0937"}],"subject":[],"published":{"date-parts":[[2020]]},"assertion":[{"value":"5 June 2020","order":1,"name":"first_online","label":"First Online","group":{"name":"ChapterHistory","label":"Chapter History"}},{"value":"IPMU","order":1,"name":"conference_acronym","label":"Conference Acronym","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"International Conference on Information Processing and Management of Uncertainty in Knowledge-Based Systems","order":2,"name":"conference_name","label":"Conference Name","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"Lisbon","order":3,"name":"conference_city","label":"Conference City","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"Portugal","order":4,"name":"conference_country","label":"Conference Country","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"2020","order":5,"name":"conference_year","label":"Conference Year","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"15 June 2020","order":7,"name":"conference_start_date","label":"Conference Start Date","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"19 June 2020","order":8,"name":"conference_end_date","label":"Conference End Date","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"18","order":9,"name":"conference_number","label":"Conference Number","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"ipmu2020","order":10,"name":"conference_id","label":"Conference ID","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"https:\/\/ipmu2020.inesc-id.pt\/","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":"213","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":"146","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":"27","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":"69% - 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":"3,2","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":"4","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":"The IPMU 2020 was held virtually due to the coronavirus pandemic.","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)"}},{"value":"This content has been made available to all.","name":"free","label":"Free to read"}]}}