{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,8,20]],"date-time":"2025-08-20T12:25:15Z","timestamp":1755692715288,"version":"3.40.5"},"reference-count":43,"publisher":"Elsevier BV","license":[{"start":{"date-parts":[[2014,9,1]],"date-time":"2014-09-01T00:00:00Z","timestamp":1409529600000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/www.elsevier.com\/tdm\/userlicense\/1.0\/"}],"content-domain":{"domain":["elsevier.com","sciencedirect.com"],"crossmark-restriction":true},"short-container-title":["Engineering Applications of Artificial Intelligence"],"published-print":{"date-parts":[[2014,9]]},"DOI":"10.1016\/j.engappai.2014.06.001","type":"journal-article","created":{"date-parts":[[2014,6,28]],"date-time":"2014-06-28T05:02:44Z","timestamp":1403931764000},"page":"178-192","update-policy":"https:\/\/doi.org\/10.1016\/elsevier_cm_policy","source":"Crossref","is-referenced-by-count":13,"special_numbering":"C","title":["Enhancing data stream predictions with reliability estimators and explanation"],"prefix":"10.1016","volume":"34","author":[{"given":"Zoran","family":"Bosni\u0107","sequence":"first","affiliation":[]},{"given":"Jaka","family":"Dem\u0161ar","sequence":"additional","affiliation":[]},{"ORCID":"https:\/\/orcid.org\/0000-0002-3436-5003","authenticated-orcid":false,"given":"Grega","family":"Ke\u0161pret","sequence":"additional","affiliation":[]},{"ORCID":"https:\/\/orcid.org\/0000-0001-7867-6682","authenticated-orcid":false,"given":"Pedro","family":"Pereira Rodrigues","sequence":"additional","affiliation":[]},{"ORCID":"https:\/\/orcid.org\/0000-0003-3357-1195","authenticated-orcid":false,"given":"Jo\u00e3o","family":"Gama","sequence":"additional","affiliation":[]},{"given":"Igor","family":"Kononenko","sequence":"additional","affiliation":[]}],"member":"78","reference":[{"key":"10.1016\/j.engappai.2014.06.001_bib1","doi-asserted-by":"crossref","first-page":"373","DOI":"10.1016\/0950-7051(96)81920-4","article-title":"Survey and critique of techniques for extracting rules from trained artificial neural networks","volume":"8","author":"Andrews","year":"1995","journal-title":"Knowl.-Based Syst."},{"key":"10.1016\/j.engappai.2014.06.001_bib2","unstructured":"Becker, B., Kohavi, R., Sommerfield, D., 1997. Visualizing the simple Bayesian classier. In: KDD Workshop on Issues in the Integration of Data Mining and Data Visualization."},{"key":"10.1016\/j.engappai.2014.06.001_bib3","first-page":"1601","article-title":"Moa: Massive online analysis","volume":"11","author":"Bifet","year":"2010","journal-title":"J. Mach. Learn. Res."},{"key":"10.1016\/j.engappai.2014.06.001_bib4","doi-asserted-by":"crossref","first-page":"504","DOI":"10.1016\/j.datak.2008.08.001","article-title":"Comparison of approaches for estimating reliability of individual regression prediction","volume":"67","author":"Bosni\u0107","year":"2008","journal-title":"Data Knowl. Eng."},{"key":"10.1016\/j.engappai.2014.06.001_bib5","doi-asserted-by":"crossref","first-page":"187","DOI":"10.1007\/s10489-007-0084-9","article-title":"Estimation of individual prediction reliability using the local sensitivity analysis","volume":"29","author":"Bosni\u0107","year":"2008","journal-title":"Appl. Intell."},{"key":"10.1016\/j.engappai.2014.06.001_bib6","doi-asserted-by":"crossref","first-page":"385","DOI":"10.3233\/IDA-2009-0371","article-title":"An overview of advances in reliability estimation of individual predictions in machine learning","volume":"13","author":"Bosni\u0107","year":"2009","journal-title":"Intell. Data Anal."},{"key":"10.1016\/j.engappai.2014.06.001_bib7","doi-asserted-by":"crossref","first-page":"248","DOI":"10.1109\/TITB.2011.2164546","article-title":"Mining data from hemodynamic simulations for generating prediction and explanation models","volume":"2","author":"Bosni\u0107","year":"2012","journal-title":"IEEE Trans. Inf. Technol. Biomed.: A Publ. IEEE Eng. Med. Biol. Soc."},{"key":"10.1016\/j.engappai.2014.06.001_bib8","first-page":"499","article-title":"Stability and generalization","volume":"2","author":"Bousquet","year":"2002","journal-title":"J. Mach. Learn. Res."},{"key":"10.1016\/j.engappai.2014.06.001_bib9","doi-asserted-by":"crossref","first-page":"5","DOI":"10.1023\/A:1010933404324","article-title":"Random forests","volume":"45","author":"Breiman","year":"2001","journal-title":"Mach. Learn. J."},{"year":"1985","series-title":"Comparative Models for Electrical Load Forecasting","author":"Bunn","key":"10.1016\/j.engappai.2014.06.001_bib10"},{"key":"10.1016\/j.engappai.2014.06.001_bib11","doi-asserted-by":"crossref","unstructured":"Carney, J., Cunningham, P., 1999. Confidence and prediction intervals for neural network ensembles. In: Proceedings of IJCNN\u05f399, The International Joint Conference on Neural Networks, Washington, USA, pp. 1215\u20131218.","DOI":"10.1109\/IJCNN.1999.831133"},{"key":"10.1016\/j.engappai.2014.06.001_bib12","doi-asserted-by":"crossref","unstructured":"Craven, M.W., Shavlik, J., 1994. Using sampling and queries to extract rules from trained neural networks. In: Proceedings of International Conference on Machine Learning, pp. 37\u201345.","DOI":"10.1016\/B978-1-55860-335-6.50013-1"},{"year":"2002","series-title":"An R and S Plus Companion to Applied Regression","author":"Fox","key":"10.1016\/j.engappai.2014.06.001_bib13"},{"year":"2010","series-title":"Knowledge Discovery from Data Streams","author":"Gama","key":"10.1016\/j.engappai.2014.06.001_bib14"},{"year":"2007","series-title":"Learning from Data Streams \u2013 Processing Techniques in Sensor Networks","author":"Gama","key":"10.1016\/j.engappai.2014.06.001_bib15"},{"key":"10.1016\/j.engappai.2014.06.001_bib16","doi-asserted-by":"crossref","first-page":"317","DOI":"10.1007\/s10994-012-5320-9","article-title":"On evaluating stream learning algorithms","volume":"90","author":"Gama","year":"2013","journal-title":"Mach. Learn."},{"key":"10.1016\/j.engappai.2014.06.001_bib17","unstructured":"Gammerman, A., Vovk, V., Vapnik, V., 1998. Learning by transduction. In: Proceedings of the 14th Conference on Uncertainty in Artificial Intelligence, Madison, Wisconsin, pp. 148\u2013155."},{"key":"10.1016\/j.engappai.2014.06.001_bib18","doi-asserted-by":"crossref","unstructured":"Hamel, L., 2006. Visualization of support vector machines with unsupervised learning. In: Proceedings of 2006 IEEE Symposium on Computational Intelligence in Bioinformatics and Computational Biology, Toronto, Canada, pp. 1\u20138.","DOI":"10.1109\/CIBCB.2006.330984"},{"key":"10.1016\/j.engappai.2014.06.001_bib19","series-title":"Advances in Neural Information Processing Systems","first-page":"176","article-title":"Practical confidence and prediction intervals","author":"Heskes","year":"1997"},{"key":"10.1016\/j.engappai.2014.06.001_bib20","doi-asserted-by":"crossref","unstructured":"Hulten, G., Spencer, L., Domingos, P., 2001. Mining time-changing data streams. In: Proceedings of the Seventh ACM SIGKDD International Conference on Knowledge Discovery and Data Mining, pp. 97\u2013106.","DOI":"10.1145\/502512.502529"},{"key":"10.1016\/j.engappai.2014.06.001_bib21","doi-asserted-by":"crossref","unstructured":"Jakulin, A., Mo\u017eina, M., Dem\u0161ar, J., Bratko, I., Zupan, B., 2005. Nomograms for visualizing support vector machines. In: KDD \u05f305: Proceeding of the Eleventh ACM SIGKDD International Conference on Knowledge Discovery in Data Mining, ACM, New York, NY, USA. pp. 108\u2013117.","DOI":"10.1145\/1081870.1081886"},{"key":"10.1016\/j.engappai.2014.06.001_bib22","doi-asserted-by":"crossref","first-page":"317","DOI":"10.1080\/08839519308949993","article-title":"Inductive and bayesian learning in medical diagnosis","volume":"7","author":"Kononenko","year":"1993","journal-title":"Appl. Artif. Intell."},{"key":"10.1016\/j.engappai.2014.06.001_bib23","unstructured":"Kuhn, M., 2012. Variable Selection Using the Caret Package. URL \u3008http:\/\/cran.cermin.lipi.go.id\/web\/packages\/caret\/vignettes\/caretSelection.pdf\u3009."},{"key":"10.1016\/j.engappai.2014.06.001_bib24","doi-asserted-by":"crossref","first-page":"391","DOI":"10.1007\/978-3-540-36122-0_16","article-title":"Short term electric load forecasting","author":"Kyriakides","year":"2007","journal-title":"Trends Neural Comput."},{"key":"10.1016\/j.engappai.2014.06.001_bib25","doi-asserted-by":"crossref","unstructured":"Lemaire, V., F\u00e9raud, R., Voisine, N., 2008. Contact personalization using a score understanding method. In: International Joint Conference on Neural Networks (IJCNN).","DOI":"10.1109\/IJCNN.2008.4633863"},{"key":"10.1016\/j.engappai.2014.06.001_bib26","doi-asserted-by":"crossref","first-page":"1686","DOI":"10.1109\/TPAMI.2005.224","article-title":"Open set face recognition using transduction","volume":"27","author":"Li","year":"2005","journal-title":"IEEE Trans. Pattern Anal. Mach. Intell."},{"key":"10.1016\/j.engappai.2014.06.001_bib27","doi-asserted-by":"crossref","unstructured":"Mo\u017eina, M., Dem\u0161ar, J., Kattan, M., Zupan, B., 2004. Nomograms for visualization of naive bayesian classifier. In: PKDD \u05f304: Proceedings of the 8th European Conference on Principles and Practice of Knowledge Discovery in Databases, Springer-Verlag New York, Inc., New York, NY, USA, pp. 337\u2013348.","DOI":"10.1007\/978-3-540-30116-5_32"},{"key":"10.1016\/j.engappai.2014.06.001_bib28","unstructured":"Nouretdinov, I., Melluish, T., Vovk, V., 2001. Ridge regression confidence machine. In: Proceedings of 18th International Conference on Machine Learning. Morgan Kaufmann, San Francisco, CA, pp. 385\u2013392."},{"key":"10.1016\/j.engappai.2014.06.001_bib29","unstructured":"NYISO, 2012. New York Independent System Operator. Load Data. URL \u3008http:\/\/www.nyiso.com\/public\/markets_operations\/market_data\/load_data\/index.jsp\u3009."},{"key":"10.1016\/j.engappai.2014.06.001_bib30","doi-asserted-by":"crossref","unstructured":"Poulet, F., 2004. SVM and graphical algorithms: a cooperative approach. In: Proceedings of Fourth IEEE International Conference on Data Mining, pp. 499\u2013502.","DOI":"10.1109\/ICDM.2004.10068"},{"key":"10.1016\/j.engappai.2014.06.001_bib31","doi-asserted-by":"crossref","first-page":"589","DOI":"10.1109\/TKDE.2007.190734","article-title":"Explaining classifications for individual instances","volume":"20","author":"Robnik-\u0160ikonja","year":"2008","journal-title":"IEEE Trans. Knowl. Data Eng."},{"key":"10.1016\/j.engappai.2014.06.001_bib32","doi-asserted-by":"crossref","unstructured":"Rodrigues, P., Bosni\u0107, Z., Gama, J., 2008. Online reliability estimates for individual predictions in data streams. In: Bonchi, F. (Ed.), ICDM Workshops 2008: Proceedings, Pisa, Italy. pp. 36\u201345.","DOI":"10.1109\/ICDMW.2008.123"},{"key":"10.1016\/j.engappai.2014.06.001_bib33","doi-asserted-by":"crossref","first-page":"477","DOI":"10.3233\/IDA-2009-0377","article-title":"A system for analysis and prediction of electricity load streams","volume":"13","author":"Rodrigues","year":"2009","journal-title":"Intell. Data Anal."},{"key":"10.1016\/j.engappai.2014.06.001_bib34","unstructured":"Rodrigues, P., Gama, J., Sebastiao, R., 2010. Memoryless fading windows in ubiquitous settings. In: Proceedings of Ubiquitous Data Mining (UDM) Workshop in Conjunction with the 19th ECAI 2010, Lisbon, pp. 27\u201332."},{"key":"10.1016\/j.engappai.2014.06.001_bib35","doi-asserted-by":"crossref","first-page":"91","DOI":"10.1016\/j.datak.2006.10.005","article-title":"Strategies for improving the modeling and interpretability of bayesian networks","volume":"63","author":"de Santana","year":"2007","journal-title":"Data Knowl. Eng."},{"key":"10.1016\/j.engappai.2014.06.001_bib36","unstructured":"Saunders, C., Gammerman, A., Vovk, V., 1999. Transduction with confidence and credibility. In: Proceedings of IJCAI\u05f399, pp. 722\u2013726."},{"key":"10.1016\/j.engappai.2014.06.001_bib37","unstructured":"Sebasti\u00e3o, R., Gama, J., 2009. A study on change detection methods. In: Lopes, L.S., Lau, N., Mariano, P., Rocha, L.M. (Eds.), Progress in Artificial Intelligence, 14th Portuguese Conference on Artificial Intelligence, EPIA 2009, Aveiro, Portugal, October 12\u201315, 2009. Proceedings, Springer, pp. 353\u2013264."},{"key":"10.1016\/j.engappai.2014.06.001_bib38","doi-asserted-by":"crossref","unstructured":"Street, W.N., Kim, Y., 2001. A streaming ensemble algorithm (sea) for large-scale classification. In: Proceedings of the Seventh ACM SIGKDD International Conference on Knowledge Discovery and Data Mining. ACM, New York, NY, USA, pp. 377\u2013382.","DOI":"10.1145\/502512.502568"},{"key":"10.1016\/j.engappai.2014.06.001_bib39","doi-asserted-by":"crossref","first-page":"71","DOI":"10.1007\/BF00993103","article-title":"Extracting refined rules from knowledge-based neural networks, machine learning","volume":"13","author":"Towell","year":"1993","journal-title":"Mach. Learn."},{"key":"10.1016\/j.engappai.2014.06.001_bib40","doi-asserted-by":"crossref","first-page":"305","DOI":"10.1007\/s10115-009-0244-9","article-title":"Explanation and reliability of prediction models","volume":"9","author":"\u0160trumbelj","year":"2010","journal-title":"Knowl. Inf. Syst."},{"key":"10.1016\/j.engappai.2014.06.001_bib41","first-page":"1","article-title":"An efficient explanation of individual classifications using game theory","volume":"11","author":"\u0160trumbelj","year":"2010","journal-title":"J. Mach. Learn. Res."},{"key":"10.1016\/j.engappai.2014.06.001_bib42","doi-asserted-by":"crossref","first-page":"886","DOI":"10.1016\/j.datak.2009.01.004","article-title":"Explaining instance classifications with interactions of subsets of feature values","volume":"68","author":"\u0160trumbelj","year":"2009","journal-title":"Data Knowl. Eng."},{"key":"10.1016\/j.engappai.2014.06.001_bib43","doi-asserted-by":"crossref","unstructured":"Weigend, A., Nix, D., 1994. Predictions with confidence intervals (local error bars). In: Proceedings of the International Conference on Neural Information Processing (ICONIP\u05f394). Seoul, Korea, pp. 847\u2013852.","DOI":"10.21236\/ADA451363"}],"container-title":["Engineering Applications of Artificial Intelligence"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/api.elsevier.com\/content\/article\/PII:S0952197614001237?httpAccept=text\/xml","content-type":"text\/xml","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/api.elsevier.com\/content\/article\/PII:S0952197614001237?httpAccept=text\/plain","content-type":"text\/plain","content-version":"vor","intended-application":"text-mining"}],"deposited":{"date-parts":[[2019,8,11]],"date-time":"2019-08-11T20:47:15Z","timestamp":1565556435000},"score":1,"resource":{"primary":{"URL":"https:\/\/linkinghub.elsevier.com\/retrieve\/pii\/S0952197614001237"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2014,9]]},"references-count":43,"alternative-id":["S0952197614001237"],"URL":"https:\/\/doi.org\/10.1016\/j.engappai.2014.06.001","relation":{},"ISSN":["0952-1976"],"issn-type":[{"type":"print","value":"0952-1976"}],"subject":[],"published":{"date-parts":[[2014,9]]},"assertion":[{"value":"Elsevier","name":"publisher","label":"This article is maintained by"},{"value":"Enhancing data stream predictions with reliability estimators and explanation","name":"articletitle","label":"Article Title"},{"value":"Engineering Applications of Artificial Intelligence","name":"journaltitle","label":"Journal Title"},{"value":"https:\/\/doi.org\/10.1016\/j.engappai.2014.06.001","name":"articlelink","label":"CrossRef DOI link to publisher maintained version"},{"value":"article","name":"content_type","label":"Content Type"},{"value":"Copyright \u00a9 2014 Elsevier Ltd. All rights reserved.","name":"copyright","label":"Copyright"}]}}