{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,3,6]],"date-time":"2026-03-06T10:23:15Z","timestamp":1772792595025,"version":"3.50.1"},"publisher-location":"Cham","reference-count":17,"publisher":"Springer International Publishing","isbn-type":[{"value":"9783319653396","type":"print"},{"value":"9783319653402","type":"electronic"}],"license":[{"start":{"date-parts":[[2017,1,1]],"date-time":"2017-01-01T00:00:00Z","timestamp":1483228800000},"content-version":"tdm","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":[[2017]]},"DOI":"10.1007\/978-3-319-65340-2_42","type":"book-chapter","created":{"date-parts":[[2017,8,8]],"date-time":"2017-08-08T11:49:29Z","timestamp":1502192969000},"page":"513-524","update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":4,"title":["Exploring Resampling with Neighborhood Bias on Imbalanced Regression Problems"],"prefix":"10.1007","author":[{"given":"Paula","family":"Branco","sequence":"first","affiliation":[]},{"given":"Lu\u00eds","family":"Torgo","sequence":"additional","affiliation":[]},{"given":"Rita P.","family":"Ribeiro","sequence":"additional","affiliation":[]}],"member":"297","published-online":{"date-parts":[[2017,8,9]]},"reference":[{"key":"42_CR1","unstructured":"Branco, P.: Re-sampling approaches for regression tasks under imbalanced domains. Master\u2019s thesis, Department of Computer Science, Faculty of Sciences - University of Porto (2014)"},{"key":"42_CR2","unstructured":"Branco, P., Ribeiro, R.P., Torgo, L.: UBL: an R package for utility-based learning. arXiv preprint arXiv:1604.08079 (2016)"},{"issue":"2","key":"42_CR3","first-page":"31","volume":"49","author":"P Branco","year":"2016","unstructured":"Branco, P., Torgo, L., Ribeiro, R.P.: A survey of predictive modeling on imbalanced domains. ACM Comput. Surv. (CSUR) 49(2), 31 (2016)","journal-title":"ACM Comput. Surv. (CSUR)"},{"key":"42_CR4","doi-asserted-by":"publisher","first-page":"321","DOI":"10.1613\/jair.953","volume":"16","author":"NV Chawla","year":"2002","unstructured":"Chawla, N.V., Bowyer, K.W., Hall, L.O., Kegelmeyer, W.P.: SMOTE: synthetic minority over-sampling technique. JAIR 16, 321\u2013357 (2002)","journal-title":"JAIR"},{"key":"42_CR5","unstructured":"Dimitriadou, E., Hornik, K., Leisch, F., Meyer, D., Weingessel, A.: e1071: Misc Functions of the Department of Statistics (e1071), TU Wien (2011)"},{"key":"42_CR6","doi-asserted-by":"crossref","unstructured":"He, H., Bai, Y., Garcia, E.A., Li, S.: ADASYN: adaptive synthetic sampling approach for imbalanced learning. In: IEEE International Joint Conference on Neural Networks, pp. 1322\u20131328. IEEE (2008)","DOI":"10.1109\/IJCNN.2008.4633969"},{"issue":"9","key":"42_CR7","doi-asserted-by":"publisher","first-page":"1263","DOI":"10.1109\/TKDE.2008.239","volume":"21","author":"H He","year":"2009","unstructured":"He, H., Garcia, E.A.: Learning from imbalanced data. IEEE Trans. Knowl. Data Eng. 21(9), 1263\u20131284 (2009)","journal-title":"IEEE Trans. Knowl. Data Eng."},{"key":"42_CR8","doi-asserted-by":"publisher","first-page":"1","DOI":"10.1007\/s13748-016-0094-0","volume":"5","author":"B Krawczyk","year":"2016","unstructured":"Krawczyk, B.: Learning from imbalanced data: open challenges and future directions. Prog. Artif. Intell. 5, 1\u201312 (2016)","journal-title":"Prog. Artif. Intell."},{"issue":"3","key":"42_CR9","first-page":"18","volume":"2","author":"A Liaw","year":"2002","unstructured":"Liaw, A., Wiener, M.: Classification and regression by randomforest. R News 2(3), 18\u201322 (2002)","journal-title":"R News"},{"key":"42_CR10","doi-asserted-by":"publisher","first-page":"113","DOI":"10.1016\/j.ins.2013.07.007","volume":"250","author":"V L\u00f3pez","year":"2013","unstructured":"L\u00f3pez, V., Fern\u00e1ndez, A., Garc\u00eda, S., Palade, V., Herrera, F.: An insight into classification with imbalanced data: empirical results and current trends on using data intrinsic characteristics. Inf. Sci. 250, 113\u2013141 (2013)","journal-title":"Inf. Sci."},{"key":"42_CR11","unstructured":"Milborrow, S.: earth: Multivariate Adaptive Regression Spline Models. Derived from mda:mars by Trevor Hastie and Rob Tibshirani (2012)"},{"key":"42_CR12","unstructured":"Ribeiro, R.P.: Utility-based regression. Ph.D. thesis, Department Computer Science, Faculty of Sciences, University of Porto (2011)"},{"key":"42_CR13","unstructured":"Torgo, L.: An infra-structure for performance estimation and experimental comparison of predictive models in r. CoRR abs\/1412.0436 (2014)"},{"key":"42_CR14","series-title":"Lecture Notes in Computer Science","doi-asserted-by":"publisher","first-page":"332","DOI":"10.1007\/978-3-642-04747-3_26","volume-title":"Discovery Science","author":"L Torgo","year":"2009","unstructured":"Torgo, L., Ribeiro, R.P.: Precision and recall for regression. In: Gama, J., Costa, V.S., Jorge, A.M., Brazdil, P.B. (eds.) DS 2009. LNCS, vol. 5808, pp. 332\u2013346. Springer, Heidelberg (2009). doi:10.1007\/978-3-642-04747-3_26"},{"issue":"3","key":"42_CR15","doi-asserted-by":"publisher","first-page":"465","DOI":"10.1111\/exsy.12081","volume":"32","author":"L Torgo","year":"2015","unstructured":"Torgo, L., Branco, P., Ribeiro, R.P., Pfahringer, B.: Resampling strategies for regression. Expert Syst. 32(3), 465\u2013476 (2015)","journal-title":"Expert Syst."},{"key":"42_CR16","series-title":"Lecture Notes in Computer Science","doi-asserted-by":"publisher","first-page":"597","DOI":"10.1007\/978-3-540-74976-9_63","volume-title":"Knowledge Discovery in Databases: PKDD 2007","author":"L Torgo","year":"2007","unstructured":"Torgo, L., Ribeiro, R.P.: Utility-based regression. In: Kok, J.N., Koronacki, J., Lopez de Mantaras, R., Matwin, S., Mladeni\u010d, D., Skowron, A. (eds.) PKDD 2007. LNCS, vol. 4702, pp. 597\u2013604. Springer, Heidelberg (2007). doi:10.1007\/978-3-540-74976-9_63"},{"key":"42_CR17","series-title":"Lecture Notes in Computer Science","doi-asserted-by":"publisher","first-page":"378","DOI":"10.1007\/978-3-642-40669-0_33","volume-title":"Progress in Artificial Intelligence","author":"L Torgo","year":"2013","unstructured":"Torgo, L., Ribeiro, R.P., Pfahringer, B., Branco, P.: SMOTE for regression. In: Correia, L., Reis, L.P., Cascalho, J. (eds.) EPIA 2013. LNCS, vol. 8154, pp. 378\u2013389. Springer, Heidelberg (2013). doi:10.1007\/978-3-642-40669-0_33"}],"container-title":["Lecture Notes in Computer Science","Progress in Artificial Intelligence"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/978-3-319-65340-2_42","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2026,3,6]],"date-time":"2026-03-06T07:49:43Z","timestamp":1772783383000},"score":1,"resource":{"primary":{"URL":"https:\/\/link.springer.com\/10.1007\/978-3-319-65340-2_42"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2017]]},"ISBN":["9783319653396","9783319653402"],"references-count":17,"URL":"https:\/\/doi.org\/10.1007\/978-3-319-65340-2_42","relation":{},"ISSN":["0302-9743","1611-3349"],"issn-type":[{"value":"0302-9743","type":"print"},{"value":"1611-3349","type":"electronic"}],"subject":[],"published":{"date-parts":[[2017]]},"assertion":[{"value":"9 August 2017","order":1,"name":"first_online","label":"First Online","group":{"name":"ChapterHistory","label":"Chapter History"}},{"value":"EPIA","order":1,"name":"conference_acronym","label":"Conference Acronym","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"EPIA Conference on Artificial Intelligence","order":2,"name":"conference_name","label":"Conference Name","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"Porto","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":"2017","order":5,"name":"conference_year","label":"Conference Year","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"5 September 2017","order":7,"name":"conference_start_date","label":"Conference Start Date","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"8 September 2017","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":"epia2017","order":10,"name":"conference_id","label":"Conference ID","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"https:\/\/web.fe.up.pt\/~epia2017\/","order":11,"name":"conference_url","label":"Conference URL","group":{"name":"ConferenceInfo","label":"Conference Information"}}]}}