{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,6,11]],"date-time":"2025-06-11T07:29:53Z","timestamp":1749626993704},"publisher-location":"Berlin, Heidelberg","reference-count":17,"publisher":"Springer Berlin Heidelberg","isbn-type":[{"type":"print","value":"9783540205906"},{"type":"electronic","value":"9783540245865"}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":[],"published-print":{"date-parts":[[2003]]},"DOI":"10.1007\/978-3-540-24586-5_52","type":"book-chapter","created":{"date-parts":[[2011,1,7]],"date-time":"2011-01-07T05:09:21Z","timestamp":1294376961000},"page":"424-431","source":"Crossref","is-referenced-by-count":15,"title":["Restricted Decontamination for the Imbalanced Training Sample Problem"],"prefix":"10.1007","author":[{"given":"R.","family":"Barandela","sequence":"first","affiliation":[]},{"given":"E.","family":"Rangel","sequence":"additional","affiliation":[]},{"given":"J. S.","family":"S\u00e1nchez","sequence":"additional","affiliation":[]},{"given":"F. J.","family":"Ferri","sequence":"additional","affiliation":[]}],"member":"297","reference":[{"key":"52_CR1","unstructured":"Barandela, R.: The Nearest Neighbor rule: an empirical study of its methodological aspects. PhD thesis, Univ. Berlin (1987)"},{"key":"52_CR2","volume-title":"Pattern Recognition and String Matching","author":"R. Barandela","year":"2003","unstructured":"Barandela, R., Gasca, E., Alejo, R.: Correcting the training data. In: Chen, D., Cheng, X. (eds.) Pattern Recognition and String Matching, Kluwer, The Netherlands (2003)"},{"key":"52_CR3","doi-asserted-by":"crossref","unstructured":"Barandela, R., S\u00e1nchez, J.S., Valdovinos, R.M.: New applications of ensembles of classifiers. Pattern Analysis and Applications (2003) (to appear)","DOI":"10.1007\/s10044-003-0192-z"},{"key":"52_CR4","doi-asserted-by":"publisher","first-page":"849","DOI":"10.1016\/S0031-3203(02)00257-1","volume":"36","author":"R. Barandela","year":"2003","unstructured":"Barandela, R., S\u00e1nchez, J.S., Garc\u00eda, V., Rangel, E.: Strategies for learning in class imbalance problems. Pattern Recognition\u00a036, 849\u2013851 (2003)","journal-title":"Pattern Recognition"},{"key":"52_CR5","doi-asserted-by":"crossref","first-page":"321","DOI":"10.1613\/jair.953","volume":"16","author":"N.V. Chawla","year":"2000","unstructured":"Chawla, N.V., Bowyer, K.W., Hall, L.O., Kegelmeyer, W.P.: SMOTE: synthetic minority over-sampling technique. Journal of Artificial Intelligence Research\u00a016, 321\u2013357 (2000)","journal-title":"Journal of Artificial Intelligence Research"},{"key":"52_CR6","unstructured":"Merz, C.J., Murphy, P.M.: Uci repository of machine learning databases. Technical report, University of California at Irvine, Department of Information and Computer Science (1998)"},{"key":"52_CR7","series-title":"TR WS-00-05","volume-title":"Workshop on Learning from Imbalanced Data Sets","author":"T. Eavis","year":"2000","unstructured":"Eavis, T., Japkowicz, N.: A recognition-based alternative to discriminationbased multi-layer perceptrons. In: Workshop on Learning from Imbalanced Data Sets. TR WS-00-05, AAAI Press, Menlo Park (2000)"},{"key":"52_CR8","unstructured":"Ezawa, K.J., Singh, M., Norton, S.W.: Learning goal oriented bayesian networks for telecommunications management. In: Proc. 13th Int. Conf. on Machine Learning, pp. 139\u2013147 (1996)"},{"key":"52_CR9","doi-asserted-by":"publisher","first-page":"291","DOI":"10.1023\/A:1009700419189","volume":"1","author":"T. Fawcett","year":"1996","unstructured":"Fawcett, T., Provost, F.: Adaptive fraud detection. Data Mining and Knowledge Discovery\u00a01, 291\u2013316 (1996)","journal-title":"Data Mining and Knowledge Discovery"},{"key":"52_CR10","volume-title":"Construction and assessment of classification rules","author":"D.J. Hand","year":"1997","unstructured":"Hand, D.J.: Construction and assessment of classification rules. John Wiley and Sons, Chichester (1997)"},{"key":"52_CR11","unstructured":"Koplowitz, J., Brown, T.A.: On the relation of performance to editing in nearest neighbor rules. In: Proceedings of the 4th International Joint Conference on Pattern Recognition (1978)"},{"key":"52_CR12","doi-asserted-by":"publisher","first-page":"195","DOI":"10.1023\/A:1007452223027","volume":"30","author":"M. Kubat","year":"1998","unstructured":"Kubat, M., Holte, R., Matwin, S.: Detection of oil-spills in radar images of sea surface. Machine Learning\u00a030, 195\u2013215 (1998)","journal-title":"Machine Learning"},{"key":"52_CR13","unstructured":"Kubat, M., Matwin, S.: Addressing the curse of imbalanced training sets: One sided selection. In: Proceedings of the 14th International Conference on Machine Learning, pp. 179\u2013186 (1997)"},{"key":"52_CR14","unstructured":"Mladenic, D., Grobelnik, M.: Feature selection for unbalanced class distribution and naive bayes. In: Proc. 16th Int. Conf. on Machine Learning, pp. 258\u2013267 (1999)"},{"key":"52_CR15","doi-asserted-by":"crossref","unstructured":"Pazzani, M., Merz, C., Murphy, P., Ali, K., Hume, T., Brunk, C.: Reducing misclassification costs. In: Proc 11th Int. Conf. on Machine Learning, pp. 217\u2013225 (1994)","DOI":"10.1016\/B978-1-55860-335-6.50034-9"},{"key":"52_CR16","doi-asserted-by":"crossref","unstructured":"Wilson, D.L.: Asymptotic properties of nearest neighbor rules using edited data\u00a02(3), 408\u2013421 (1972)","DOI":"10.1109\/TSMC.1972.4309137"},{"key":"52_CR17","doi-asserted-by":"publisher","first-page":"1417","DOI":"10.1142\/S0218001493000698","volume":"7","author":"K. Woods","year":"1993","unstructured":"Woods, K., Doss, C., Bowyer, K.W., Solka, J., Priebe, C., Kegelmeyer, W.P.: Comparative evaluation of pattern recognition techniques for detection of micro calcifications in mammography. International Journal of Pattern Recognition and Artificial Intelligence\u00a07, 1417\u20131436 (1993)","journal-title":"International Journal of Pattern Recognition and Artificial Intelligence"}],"container-title":["Lecture Notes in Computer Science","Progress in Pattern Recognition, Speech and Image Analysis"],"original-title":[],"link":[{"URL":"http:\/\/link.springer.com\/content\/pdf\/10.1007\/978-3-540-24586-5_52","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2019,6,7]],"date-time":"2019-06-07T17:09:18Z","timestamp":1559927358000},"score":1,"resource":{"primary":{"URL":"http:\/\/link.springer.com\/10.1007\/978-3-540-24586-5_52"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2003]]},"ISBN":["9783540205906","9783540245865"],"references-count":17,"URL":"https:\/\/doi.org\/10.1007\/978-3-540-24586-5_52","relation":{},"ISSN":["0302-9743","1611-3349"],"issn-type":[{"type":"print","value":"0302-9743"},{"type":"electronic","value":"1611-3349"}],"subject":[],"published":{"date-parts":[[2003]]}}}