{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,8,17]],"date-time":"2026-08-17T14:59:30Z","timestamp":1786978770532,"version":"3.56.0"},"publisher-location":"Cham","reference-count":37,"publisher":"Springer International Publishing","isbn-type":[{"value":"9783030598532","type":"print"},{"value":"9783030598549","type":"electronic"}],"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\/978-3-030-59854-9_8","type":"book-chapter","created":{"date-parts":[[2020,11,2]],"date-time":"2020-11-02T18:02:42Z","timestamp":1604340162000},"page":"96-114","update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":4,"title":["Loss-Size and Reliability Trade-Offs Amongst Diverse Redundant Binary Classifiers"],"prefix":"10.1007","author":[{"given":"Kizito","family":"Salako","sequence":"first","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"297","published-online":{"date-parts":[[2020,11,3]]},"reference":[{"key":"8_CR1","doi-asserted-by":"publisher","first-page":"138","DOI":"10.1198\/016214505000000907","volume":"101","author":"P Bartlett","year":"2006","unstructured":"Bartlett, P., Jordan, M., McAuliffe, J.: Convexity, classification, and risk bounds. J. Am. Stat. Assoc. 101, 138\u2013156 (2006). https:\/\/doi.org\/10.1198\/016214505000000907","journal-title":"J. Am. Stat. Assoc."},{"issue":"5","key":"8_CR2","doi-asserted-by":"publisher","first-page":"708","DOI":"10.1109\/TSE.2010.67","volume":"37","author":"P Bishop","year":"2011","unstructured":"Bishop, P., Bloomfield, R., Littlewood, B., Povyakalo, A., Wright, D.: Toward a formalism for conservative claims about the dependability of software-based systems. IEEE Trans. Softw. Eng. 37(5), 708\u2013717 (2011)","journal-title":"IEEE Trans. Softw. Eng."},{"key":"8_CR3","doi-asserted-by":"publisher","unstructured":"Blough, D.M., Sullivan, G.F.: A comparison of voting strategies for fault-tolerant distributed systems. In: Proceedings Ninth Symposium on Reliable Distributed Systems, pp. 136\u2013145 (1990). https:\/\/doi.org\/10.1109\/RELDIS.1990.93959","DOI":"10.1109\/RELDIS.1990.93959"},{"key":"8_CR4","doi-asserted-by":"publisher","unstructured":"Box, G.E., Tiao, G.C.: Nature of Bayesian Inference, chap. 1, pp. 1\u201375. Wiley (2011). https:\/\/doi.org\/10.1002\/9781118033197.ch1","DOI":"10.1002\/9781118033197.ch1"},{"key":"8_CR5","doi-asserted-by":"publisher","first-page":"249","DOI":"10.1016\/j.neunet.2018.07.011","volume":"106","author":"M Buda","year":"2018","unstructured":"Buda, M., Maki, A., Mazurowski, M.A.: A systematic study of the class imbalance problem in convolutional neural networks. Neural Netw. 106, 249\u2013259 (2018). https:\/\/doi.org\/10.1016\/j.neunet.2018.07.011","journal-title":"Neural Netw."},{"key":"8_CR6","unstructured":"Dembczy\u0144ski, K., Kot\u0142owski, W., Koyejo, O., Natarajan, N.: Consistency analysis for binary classification revisited. In: Precup, D., Teh, Y.W. (eds.) Proceedings of the 34th International Conference on Machine Learning. Proceedings of Machine Learning Research, PMLR, International Convention Centre, Sydney, Australia, vol. 70, pp. 961\u2013969, 06\u201311 August 2017. http:\/\/proceedings.mlr.press\/v70\/dembczynski17a.html"},{"key":"8_CR7","doi-asserted-by":"publisher","unstructured":"Di Giandomenico, F., Strigini, L.: Adjudicators for diverse-redundant components. In: Proceedings Ninth Symposium on Reliable Distributed Systems, pp. 114\u2013123, October 1990. https:\/\/doi.org\/10.1109\/RELDIS.1990.93957","DOI":"10.1109\/RELDIS.1990.93957"},{"key":"8_CR8","doi-asserted-by":"crossref","unstructured":"Fawcett, T.: An introduction to ROC analysis. Pattern Recogn. Lett. 27(8), 861\u2013874 (2006). http:\/\/dx.doi.org\/10.1016\/j.patrec.2005.10.010","DOI":"10.1016\/j.patrec.2005.10.010"},{"key":"8_CR9","doi-asserted-by":"publisher","unstructured":"Fawcett, T., Flach, P.A.: A response to Webb and Ting\u2019s on the application of ROC analysis to predict classification performance under varying class distributions. Mach. Learn. 58(1), 33\u201338 (2005). https:\/\/doi.org\/10.1007\/s10994-005-5256-4","DOI":"10.1007\/s10994-005-5256-4"},{"key":"8_CR10","unstructured":"Flach, P., Shaomin, W.: Repairing concavities in ROC curves. In: Proceedings of the 19th International Joint Conference on Artificial Intelligence (IJCAI 2005), IJCAI, pp. 702\u2013707, August 2005"},{"key":"8_CR11","unstructured":"Gaffney, J.E., Ulvila, J.W.: Evaluation of intrusion detectors: a decision theory approach. In: Proceedings of the 2001 IEEE Symposium on Security and Privacy, pp. 50\u201361. IEEE (2001). http:\/\/dl.acm.org\/citation.cfm?id=882495.884438"},{"issue":"6","key":"8_CR12","doi-asserted-by":"publisher","first-page":"453","DOI":"10.6028\/jres.108.040","volume":"108","author":"JE Gaffney","year":"2003","unstructured":"Gaffney, J.E., Ulvila, J.W.: Evaluation of intrusion detection systems. J. Res. Natl. Inst. Stand. Technol. 108(6), 453\u2013473 (2003)","journal-title":"J. Res. Natl. Inst. Stand. Technol."},{"key":"8_CR13","doi-asserted-by":"crossref","unstructured":"Gelman, A., Carlin, J.B., Stern, H.S., Rubin, D.B.: Bayesian Data Analysis, 2nd edn. Chapman and Hall\/CRC (2004)","DOI":"10.1201\/9780429258480"},{"issue":"1","key":"8_CR14","doi-asserted-by":"publisher","first-page":"8","DOI":"10.1111\/j.2044-8317.2011.02037.x","volume":"66","author":"A Gelman","year":"2013","unstructured":"Gelman, A., Shalizi, C.R.: Philosophy and the practice of Bayesian statistics. Br. J. Math. Stat. Psychol. 66(1), 8\u201338 (2013). https:\/\/doi.org\/10.1111\/j.2044-8317.2011.02037.x","journal-title":"Br. J. Math. Stat. Psychol."},{"issue":"2","key":"8_CR15","doi-asserted-by":"publisher","first-page":"171","DOI":"10.1023\/A:1010920819831","volume":"45","author":"DJ Hand","year":"2001","unstructured":"Hand, D.J., Till, R.J.: A simple generalisation of the area under the roc curve for multiple class classification problems. Mach. Learn. 45(2), 171\u2013186 (2001). https:\/\/doi.org\/10.1023\/A:1010920819831","journal-title":"Mach. Learn."},{"issue":"5","key":"8_CR16","doi-asserted-by":"publisher","first-page":"429","DOI":"10.3233\/IDA-2002-6504","volume":"6","author":"N Japkowicz","year":"2002","unstructured":"Japkowicz, N., Stephen, S.: The class imbalance problem: a systematic study. Intell. Data Anal. 6(5), 429\u2013449 (2002)","journal-title":"Intell. Data Anal."},{"key":"8_CR17","unstructured":"Koyejo, O.O., Natarajan, N., Ravikumar, P.K., Dhillon, I.S.: Consistent binary classification with generalized performance metrics. In: Ghahramani, Z., Welling, M., Cortes, C., Lawrence, N.D., Weinberger, K.Q. (eds.) Advances in Neural Information Processing Systems, vol. 27, pp. 2744\u20132752. Curran Associates, Inc. (2014)"},{"key":"8_CR18","doi-asserted-by":"publisher","first-page":"106752","DOI":"10.1016\/j.ress.2019.106752","volume":"197","author":"B Littlewood","year":"2020","unstructured":"Littlewood, B., Salako, K., Strigini, L., Zhao, X.: On reliability assessment when a software-based system is replaced by a thought-to-be-better one. Reliab. Eng. Syst. Saf. 197, 106752 (2020). https:\/\/doi.org\/10.1016\/j.ress.2019.106752","journal-title":"Reliab. Eng. Syst. Saf."},{"issue":"1","key":"8_CR19","first-page":"77","volume":"7","author":"HM Markowitz","year":"1952","unstructured":"Markowitz, H.M.: Portfolio selection. J. Finan. 7(1), 77\u201391 (1952)","journal-title":"J. Finan."},{"key":"8_CR20","volume-title":"Portfolio Selection, Efficient Diversification of Investments","author":"HM Markowitz","year":"1959","unstructured":"Markowitz, H.M.: Portfolio Selection, Efficient Diversification of Investments. Wiley, Hoboken (1959)"},{"key":"8_CR21","doi-asserted-by":"publisher","first-page":"169","DOI":"10.14257\/ijdta.2015.8.1.18","volume":"8","author":"J Nayak","year":"2015","unstructured":"Nayak, J., Naik, B., Behera, D.H.: A comprehensive survey on support vector machine in data mining tasks: applications and challenges. Int. J. Database Theory Appl. 8, 169\u2013186 (2015). https:\/\/doi.org\/10.14257\/ijdta.2015.8.1.18","journal-title":"Int. J. Database Theory Appl."},{"key":"8_CR22","doi-asserted-by":"publisher","unstructured":"Pouyanfar, S., et al.: A survey on deep learning: algorithms, techniques, and applications. ACM Comput. Surv. 51(5) (2018). https:\/\/doi.org\/10.1145\/3234150","DOI":"10.1145\/3234150"},{"key":"8_CR23","unstructured":"Provost, F., Fawcett, T.: Robust classification systems for imprecise environments. In: Proceedings of AAAI 1998, pp. 706\u2013713. AAAI press (1998)"},{"key":"8_CR24","unstructured":"Provost, F., Fawcett, T.: Analysis and visualization of classifier performance: comparison under imprecise class and cost distributions. In: Proceedings of the Third International Conference on Knowledge Discovery and Data Mining, KDD 1997, pp. 43\u201348. AAAI Press (1997)"},{"issue":"3","key":"8_CR25","doi-asserted-by":"publisher","first-page":"203","DOI":"10.1023\/A:1007601015854","volume":"42","author":"F Provost","year":"2001","unstructured":"Provost, F., Fawcett, T.: Robust classification for imprecise environments. Mach. Learn. 42(3), 203\u2013231 (2001). https:\/\/doi.org\/10.1023\/A:1007601015854","journal-title":"Mach. Learn."},{"key":"8_CR26","doi-asserted-by":"publisher","first-page":"34","DOI":"10.5120\/17294-7779","volume":"98","author":"R RavinderReddy","year":"2014","unstructured":"RavinderReddy, R., Kavya, B., Yellasiri, R.: A survey on SVM classifiers for intrusion detection. Int. J. Comput. Appl. 98, 34\u201344 (2014). https:\/\/doi.org\/10.5120\/17294-7779","journal-title":"Int. J. Comput. Appl."},{"key":"8_CR27","volume-title":"Measures, Integrals and Martingales","author":"R Schilling","year":"2017","unstructured":"Schilling, R.: Measures, Integrals and Martingales, 2nd edn. Cambridge University Press, Cambridge (2017)","edition":"2"},{"key":"8_CR28","doi-asserted-by":"publisher","unstructured":"Scott, M.J.J., Niranjan, M., Prager, R.W.: Realisable classifiers: improving operating performance on variable cost problems. In: Proceedings of the British Machine Vision Conference, pp. 31.1\u201331.10. BMVA Press (1998). https:\/\/doi.org\/10.5244\/C.12.31","DOI":"10.5244\/C.12.31"},{"issue":"3","key":"8_CR29","first-page":"425","volume":"19","author":"WF Sharpe","year":"1964","unstructured":"Sharpe, W.F.: Capital asset prices: a theory of market equilibrium under conditions of risk. J. Finan. 19(3), 425\u2013442 (1964)","journal-title":"J. Finan."},{"key":"8_CR30","series-title":"Lecture Notes in Computer Science","doi-asserted-by":"publisher","first-page":"106","DOI":"10.1007\/978-3-642-40793-2_10","volume-title":"Computer Safety, Reliability, and Security","author":"L Strigini","year":"2013","unstructured":"Strigini, L., Povyakalo, A.: Software fault-freeness and reliability predictions. In: Bitsch, F., Guiochet, J., Ka\u00e2niche, M. (eds.) SAFECOMP 2013. LNCS, vol. 8153, pp. 106\u2013117. Springer, Heidelberg (2013). https:\/\/doi.org\/10.1007\/978-3-642-40793-2_10"},{"key":"8_CR31","doi-asserted-by":"publisher","first-page":"66","DOI":"10.1016\/j.ress.2014.02.004","volume":"128","author":"L Strigini","year":"2014","unstructured":"Strigini, L., Wright, D.: Bounds on survival probability given mean probability of failure per demand; and the paradoxical advantages of uncertainty. Reliab. Eng. Syst. Saf. 128, 66\u201383 (2014). https:\/\/doi.org\/10.1016\/j.ress.2014.02.004","journal-title":"Reliab. Eng. Syst. Saf."},{"key":"8_CR32","doi-asserted-by":"publisher","first-page":"82","DOI":"10.1038\/scientificamerican1000-82","volume":"283","author":"J Swets","year":"2000","unstructured":"Swets, J., Dawes, R., Monahan, J.: Better decisions through science. Sci. Am. 283, 82\u201387 (2000). https:\/\/doi.org\/10.1038\/scientificamerican1000-82","journal-title":"Sci. Am."},{"issue":"4857","key":"8_CR33","doi-asserted-by":"publisher","first-page":"1285","DOI":"10.1126\/science.3287615","volume":"240","author":"JA Swets","year":"1988","unstructured":"Swets, J.A.: Measuring the accuracy of diagnostic systems. Science 240(4857), 1285\u201393 (1988)","journal-title":"Science"},{"key":"8_CR34","doi-asserted-by":"publisher","first-page":"25","DOI":"10.1007\/s10994-005-4257-7","volume":"58","author":"G Webb","year":"2005","unstructured":"Webb, G., Ting, K.: On the application of ROC analysis to predict classification performance under varying class distributions. Mach. Learn. 58, 25\u201332 (2005). https:\/\/doi.org\/10.1007\/s10994-005-4257-7","journal-title":"Mach. Learn."},{"key":"8_CR35","doi-asserted-by":"publisher","first-page":"230","DOI":"10.1016\/j.ress.2016.09.002","volume":"158","author":"X Zhao","year":"2017","unstructured":"Zhao, X., Littlewood, B., Povyakalo, A., Strigini, L., Wright, D.: Modeling the probability of failure on demand (pfd) of a 1-out-of-2 system in which one channel is \u2018quasi-perfect\u2019. Reliab. Eng. Syst. Saf. 158, 230\u2013245 (2017)","journal-title":"Reliab. Eng. Syst. Saf."},{"key":"8_CR36","doi-asserted-by":"publisher","first-page":"265","DOI":"10.1016\/j.ress.2018.03.032","volume":"175","author":"X Zhao","year":"2018","unstructured":"Zhao, X., Littlewood, B., Povyakalo, A., Strigini, L., Wright, D.: Conservative claims for the probability of perfection of a software-based system using operational experience of previous similar systems. Reliab. Eng. Syst. Saf. 175, 265\u2013282 (2018). https:\/\/doi.org\/10.1016\/j.ress.2018.03.032","journal-title":"Reliab. Eng. Syst. Saf."},{"key":"8_CR37","doi-asserted-by":"crossref","unstructured":"Zhao, X., Robu, V., Flynn, D., Salako, K., Strigini, L.: Assessing the safety and reliability of autonomous vehicles from road testing. In: The 30th International Symposium on Software Reliability Engineering (ISSRE), Berlin, Germany. IEEE (2019, in press)","DOI":"10.1109\/ISSRE.2019.00012"}],"container-title":["Lecture Notes in Computer Science","Quantitative Evaluation of Systems"],"original-title":[],"language":"en","link":[{"URL":"http:\/\/link.springer.com\/content\/pdf\/10.1007\/978-3-030-59854-9_8","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2020,12,17]],"date-time":"2020-12-17T11:12:03Z","timestamp":1608203523000},"score":1,"resource":{"primary":{"URL":"http:\/\/link.springer.com\/10.1007\/978-3-030-59854-9_8"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2020]]},"ISBN":["9783030598532","9783030598549"],"references-count":37,"URL":"https:\/\/doi.org\/10.1007\/978-3-030-59854-9_8","relation":{},"ISSN":["0302-9743","1611-3349"],"issn-type":[{"value":"0302-9743","type":"print"},{"value":"1611-3349","type":"electronic"}],"subject":[],"published":{"date-parts":[[2020]]},"assertion":[{"value":"3 November 2020","order":1,"name":"first_online","label":"First Online","group":{"name":"ChapterHistory","label":"Chapter History"}},{"value":"QEST","order":1,"name":"conference_acronym","label":"Conference Acronym","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"International Conference on Quantitative Evaluation of Systems","order":2,"name":"conference_name","label":"Conference Name","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"Vienna","order":3,"name":"conference_city","label":"Conference City","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"Austria","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":"31 August 2020","order":7,"name":"conference_start_date","label":"Conference Start Date","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"3 September 2020","order":8,"name":"conference_end_date","label":"Conference End Date","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"17","order":9,"name":"conference_number","label":"Conference Number","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"qest2020","order":10,"name":"conference_id","label":"Conference ID","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"http:\/\/www.qest.org\/qest2020\/","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":"42","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":"12","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":"7","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":"29% - 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":"3,10","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":"4,06","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)"}}]}}