{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,6,3]],"date-time":"2026-06-03T10:25:14Z","timestamp":1780482314518,"version":"3.54.1"},"reference-count":40,"publisher":"Springer Science and Business Media LLC","issue":"1","license":[{"start":{"date-parts":[[2014,4,8]],"date-time":"2014-04-08T00:00:00Z","timestamp":1396915200000},"content-version":"tdm","delay-in-days":0,"URL":"http:\/\/www.springer.com\/tdm"}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Prog Artif Intell"],"published-print":{"date-parts":[[2014,8]]},"DOI":"10.1007\/s13748-014-0045-6","type":"journal-article","created":{"date-parts":[[2014,4,7]],"date-time":"2014-04-07T21:58:39Z","timestamp":1396907919000},"page":"29-38","source":"Crossref","is-referenced-by-count":36,"title":["Undersampled $$K$$ K -means approach for handling imbalanced distributed data"],"prefix":"10.1007","volume":"3","author":[{"given":"N. Santhosh","family":"Kumar","sequence":"first","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"K. Nageswara","family":"Rao","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"A.","family":"Govardhan","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"K. Sudheer","family":"Reddy","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Ali Mirza","family":"Mahmood","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"297","published-online":{"date-parts":[[2014,4,8]]},"reference":[{"issue":"2","key":"45_CR1","doi-asserted-by":"crossref","first-page":"318","DOI":"10.1109\/TSMCB.2008.2004559","volume":"39","author":"H Xiong","year":"2009","unstructured":"Xiong, H., Wu, J.J., Chen, J.: K-means clustering versus validation measures: a data-distribution perspective. IEEE Trans. Syst. Man Cybern. B Cybern. 39(2), 318\u2013331 (2009)","journal-title":"IEEE Trans. Syst. Man Cybern. B Cybern."},{"issue":"2\u20133","key":"45_CR2","first-page":"109","volume":"395","author":"W-Z Lu","year":"2008","unstructured":"Lu, W.-Z., Wang, D.: Ground-level ozone prediction by support vector machine approach with a cost-sensitive classification scheme. Sci. Total. Environ. 395(2\u20133), 109\u2013116 (2008)","journal-title":"Sci. Total. Environ."},{"issue":"4","key":"45_CR3","doi-asserted-by":"crossref","first-page":"720","DOI":"10.1016\/j.nonrwa.2005.04.006","volume":"7","author":"Y-M Huang","year":"2006","unstructured":"Huang, Y.-M., Hung, C.-M., Jiau, H.C.: Evaluation of neural networks and data mining methods on a credit assessment task for class imbalance problem. Nonlinear Anal. R. World Appl. 7(4), 720\u2013747 (2006)","journal-title":"Nonlinear Anal. R. World Appl."},{"key":"45_CR4","doi-asserted-by":"crossref","unstructured":"Cieslak, D., Chawla, N., Striegel, A.: Combating imbalance in network intrusion datasets. In: IEEE International Conference on Granular Computing, pp. 732\u2013737 (2006)","DOI":"10.1109\/GRC.2006.1635905"},{"issue":"2\u20133","key":"45_CR5","doi-asserted-by":"crossref","first-page":"427","DOI":"10.1016\/j.neunet.2007.12.031","volume":"21","author":"MA Mazurowski","year":"2008","unstructured":"Mazurowski, M.A., Habas, P.A., Zurada, J.M., Lo, J.Y., Baker, J.A., Tourassi, G.D.: Training neural network classifiers for medical decision making: the effects of imbalanced datasets on classification performance. Neural Netw. 21(2\u20133), 427\u2013436 (2008)","journal-title":"Neural Netw."},{"key":"45_CR6","doi-asserted-by":"crossref","unstructured":"Freitas, A., Costa-Pereira, A., Brazdil, P.: Cost-sensitive decision trees applied to medical data. In: Song, I., Eder, J., Nguyen, T. (eds.) Data Warehousing Knowledge Discovery (Lecture Notes Series in Computer Science)","DOI":"10.1007\/978-3-540-74553-2_28"},{"issue":"23","key":"45_CR7","doi-asserted-by":"crossref","first-page":"5153","DOI":"10.1016\/j.ins.2007.06.030","volume":"177","author":"K Kili\u00e7","year":"2007","unstructured":"Kili\u00e7, K., Uncu, \u00d6., T\u00fcrksen, I.B.: Comparison of different strategies of utilizing fuzzy clustering in structure identification. Inf. Sci. 177(23), 5153\u20135162 (2007)","journal-title":"Inf. Sci."},{"issue":"6","key":"45_CR8","doi-asserted-by":"crossref","first-page":"362","DOI":"10.1016\/j.compmedimag.2007.01.003","volume":"31","author":"ME Celebi","year":"2007","unstructured":"Celebi, M.E., Kingravi, H.A., Uddin, B., Iyatomi, H., Aslandogan, Y.A., Stoecker, W.V., Moss, R.H.: A methodological approach to the classification of dermoscopy images. Comput. Med. Imaging Graph 31(6), 362\u2013373 (2007)","journal-title":"Comput. Med. Imaging Graph"},{"key":"45_CR9","doi-asserted-by":"crossref","unstructured":"Mahmood, A.M., Kuppa, M.R.: Early detection of clinical parameters in heart disease using improved decision tree algorithm. In: IEEE 2 $$^{nd}$$ n d Vaagdevi International Conference on Information Technology for Real World Problems (VCON\u201910) Acceptance Rate less than 6\u00a0%, pp. 24\u201329, Dec 9\u201311 Warangal. Archived in IEEE Computer Society Digital Library, India (2010)","DOI":"10.1109\/VCON.2010.12"},{"key":"45_CR10","doi-asserted-by":"crossref","unstructured":"Mahmood, A.M., Kuppa, M.R.: A novel pruning approach using expert knowledge for data specific pruning. In: Engineering with Computers, vol. 28, pp. 21\u201330. Springer-Verlag, London (2011)","DOI":"10.1007\/s00366-011-0214-1"},{"issue":"2\u2014-3","key":"45_CR11","doi-asserted-by":"crossref","first-page":"450","DOI":"10.1016\/j.neunet.2007.12.051","volume":"21","author":"X Peng","year":"2008","unstructured":"Peng, X., King, I.: Robust BMPM training based on second-order cone programming and its application in medical diagnosis. Neural Netw. 21(2\u2014-3), 450\u2013457 (2008)","journal-title":"Neural Netw."},{"key":"45_CR12","doi-asserted-by":"crossref","first-page":"321","DOI":"10.1613\/jair.953","volume":"16","author":"N Chawla","year":"2002","unstructured":"Chawla, N., Bowyer, K., Kegelmeyer, P.: Smote: synthetic minority over-sampling technique. J. Artif. Intell. Res. 16, 321\u2013357 (2002)","journal-title":"J. Artif. Intell. Res."},{"issue":"1","key":"45_CR13","doi-asserted-by":"crossref","first-page":"7","DOI":"10.1145\/1007730.1007734","volume":"6","author":"G Weiss","year":"2004","unstructured":"Weiss, G.: Mining with rarity: a unifying framework. SIGKDD Explor. Newslett. 6(1), 7\u201319 (2004)","journal-title":"SIGKDD Explor. Newslett."},{"key":"45_CR14","doi-asserted-by":"crossref","unstructured":"Guha, S., Rastogi, R., Shim, K.: Cure: an efficient clustering algorithm for large databases. In: Proceedings of International Conference on ACM Special Interest Group on Management of Data, pp. 73\u201384 (1998)","DOI":"10.1145\/276305.276312"},{"key":"45_CR15","doi-asserted-by":"crossref","first-page":"689","DOI":"10.1016\/j.patcog.2008.09.015","volume":"42","author":"MH Liu","year":"2009","unstructured":"Liu, M.H., Jiang, X.D., Kot, A.C.: A multi-prototype clustering algorithm. Pattern Recogn. 42, 689\u2013698 (2009)","journal-title":"Pattern Recogn."},{"issue":"4","key":"45_CR16","first-page":"1783","volume":"8","author":"H Xiang","year":"2012","unstructured":"Xiang, H., Yang, Y., Zhao, S.: Local clustering ensemble learning method based on improved AdaBoost for rare class analysis. J. Comput. Inform. Syst. 8(4), 1783\u20131790 (2012)","journal-title":"J. Comput. Inform. Syst."},{"issue":"7","key":"45_CR17","doi-asserted-by":"crossref","first-page":"881","DOI":"10.1109\/TPAMI.2002.1017616","volume":"24","author":"T Kanungo","year":"2002","unstructured":"Kanungo, T., Mount, D.M., Netanyahu, N.S., Piatko, C.D., Silverman, R., Wu, A.Y.: An efficient k-means clustering algorithm: analysis and implementation. IEEE Trans. Pattern Anal. Mach. Intell. 24(7), 881\u2013892 (2002)","journal-title":"IEEE Trans. Pattern Anal. Mach. Intell."},{"key":"45_CR18","doi-asserted-by":"crossref","unstructured":"de Amorim Cordeiro, R.: Minkowski metric, feature weighting and anomalous cluster initializing in K-means clustering. Pattern Recogn. 45, 1061\u20131075 (2012)","DOI":"10.1016\/j.patcog.2011.08.012"},{"key":"45_CR19","doi-asserted-by":"crossref","first-page":"3220","DOI":"10.1016\/j.eswa.2010.09.010","volume":"38","author":"S Kiranyaz","year":"2011","unstructured":"Kiranyaz, S., Ince, T., Pulkkinen, J., Gabbouj, M.: Personalized long-term ecg classification: a systematic approach. Expert Syst. Appl. 38, 3220\u20133226 (2011)","journal-title":"Expert Syst. Appl."},{"key":"45_CR20","doi-asserted-by":"crossref","first-page":"174","DOI":"10.1016\/j.proeng.2012.01.849","volume":"30","author":"AP Muniyandi","year":"2012","unstructured":"Muniyandi, A.P., Rajeswari, R., Rajaram, R.: Network anomaly detection by cascading K-means clustering and C4.5 decision tree algorithm. International Conference on Communication Technology and System Design 2011. Procedia Eng. 30, 174\u2013182 (2012)","journal-title":"Procedia Eng."},{"key":"45_CR21","unstructured":"Xuan, l., Zhigang, C., Fan, Y.: Exploring of clustering algorithm on class-imbalanced data (2013)"},{"key":"45_CR22","doi-asserted-by":"crossref","unstructured":"Bouras, C., Tsogkas, V.: A clustering technique for news articles using WordNet, Knowl. Based Syst. (2012). doi: 10.1016\/j.knosys.2012.06.015","DOI":"10.1016\/j.knosys.2012.06.015"},{"key":"45_CR23","doi-asserted-by":"crossref","first-page":"3017","DOI":"10.1016\/j.patcog.2012.02.003","volume":"45","author":"PY Mok","year":"2012","unstructured":"Mok, P.Y., Huang, H.Q., Kwok, Y.L., Au, J.S.: A robust adaptive clustering analysis method for automatic identification of clusters. Pattern Recogn. 45, 3017\u20133033 (2012)","journal-title":"Pattern Recogn."},{"key":"45_CR24","doi-asserted-by":"crossref","first-page":"196","DOI":"10.1016\/j.ins.2013.02.042","volume":"237","author":"LA Leiva","year":"2013","unstructured":"Leiva, L.A., Vidal, E.: Warped K-means: an algorithm to cluster sequentially-distributed data. Inform. Sci. 237, 196\u2013210 (2013)","journal-title":"Inform. Sci."},{"key":"45_CR25","doi-asserted-by":"crossref","first-page":"691","DOI":"10.1016\/S0167-8655(00)00131-8","volume":"22","author":"MF Jaing","year":"2001","unstructured":"Jaing, M.F., Tseng, S.S., Su, C.M.: Two phase clustering process for outlier detection. Pattern Recogn. Lett. 22, 691\u2013700 (2001)","journal-title":"Pattern Recogn. Lett."},{"key":"45_CR26","doi-asserted-by":"crossref","first-page":"2026","DOI":"10.1016\/j.sigpro.2012.07.030","volume":"93","author":"J Cao","year":"2013","unstructured":"Cao, J., Wu, Z., Wu, J., Liu, W.: Towards information-theoretic k-means clustering for image indexing. Sign. Proces. 93, 2026\u20132037 (2013)","journal-title":"Sign. Proces."},{"key":"45_CR27","doi-asserted-by":"crossref","first-page":"359","DOI":"10.1016\/j.patrec.2010.09.016","volume":"32","author":"M Mignotte","year":"2010","unstructured":"Mignotte, M.: A de-texturing and spatially constrained k-means approach for image segmentation. Pattern Recogn. Lett. 32, 359\u2013367 (2010). doi: 10.1016\/j.patrec.2010.09.016","journal-title":"Pattern Recogn. Lett."},{"key":"45_CR28","doi-asserted-by":"crossref","first-page":"113","DOI":"10.1016\/j.ins.2013.07.007","volume":"250","author":"V L\u00f3pez","year":"2013","unstructured":"L\u00f3pez, V., Fernandez, 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. Inform. Sci. 250, 113\u2013141 (2013)","journal-title":"Inform. Sci."},{"issue":"9","key":"45_CR29","doi-asserted-by":"crossref","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."},{"issue":"12","key":"45_CR30","doi-asserted-by":"crossref","first-page":"3460","DOI":"10.1016\/j.patcog.2013.05.006","volume":"46","author":"M Galar","year":"2013","unstructured":"Galar, M., Fernandez, A., Barrenechea, E., Herrera, F.: Eusboost: enhancing ensembles for highly imbalanced data-sets by evolutionary undersampling. Pattern Recogn. 46(12), 3460\u20133471 (2013)","journal-title":"Pattern Recogn."},{"issue":"4","key":"45_CR31","doi-asserted-by":"crossref","first-page":"463","DOI":"10.1109\/TSMCC.2011.2161285","volume":"42","author":"M Galar","year":"2012","unstructured":"Galar, M., Fernandez, A., Barrenechea, E., Bustince, H., Herrera, F.: A review on ensembles for class imbalance problem: bagging, boosting and hybrid based approaches. IEEE Trans. Syst. Man Cybern. Part C Appl. Rev. 42(4), 463\u2013484 (2012)","journal-title":"IEEE Trans. Syst. Man Cybern. Part C Appl. Rev."},{"key":"45_CR32","first-page":"1","volume":"7","author":"J Demsar","year":"2006","unstructured":"Demsar, J.: Statistical comparisons of classifiers over multiple data sets. J. Mach. Learning Res. 7, 1\u201330 (2006)","journal-title":"J. Mach. Learning Res."},{"key":"45_CR33","unstructured":"Garc\u00eda, S., Fernandez, A., Luengo, J., Herrera, F.: Advanced nonparametric tests for multiple comparisons in the design of experiments in computational intelligence and data mining: experimental analysis of power. Inform. Sci. 180, 2044\u20132064 (2010)"},{"key":"45_CR34","doi-asserted-by":"crossref","DOI":"10.1007\/978-0-387-09823-4","volume-title":"Data Mining And Knowledge Discovery Handbook","author":"O Maimon","year":"2010","unstructured":"Maimon, O., Rokach, L.: Data Mining And Knowledge Discovery Handbook. Springer, Berlin (2010)"},{"key":"45_CR35","volume-title":"Correlation-Based Feature Subset Selection For Machine Learning","author":"MA Hall","year":"1998","unstructured":"Hall, M.A.: Correlation-Based Feature Subset Selection For Machine Learning. Hamilton, New Zealand (1998)"},{"key":"45_CR36","volume-title":"C4.5: Programs for Machine Learning","author":"JR Quinlan","year":"1993","unstructured":"Quinlan, J.R.: C4.5: Programs for Machine Learning, 1st edn. Morgan Kaufmann Publishers, San Mateo (1993)","edition":"1"},{"key":"45_CR37","unstructured":"http:\/\/www.keel.es\/"},{"key":"45_CR38","unstructured":"Blake, C., Merz, C.J.: UCI repository of machine learning databases. Machine-readable data repository. Department of Information and Computer Science, University of California at Irvine, Irvine. http:\/\/www.ics.uci.edu\/mlearn\/MLRepository.html (2000)"},{"key":"45_CR39","volume-title":"Data Mining: Practical Machine Learning Tools and Techniques","author":"IH Witten","year":"2005","unstructured":"Witten, I.H., Frank, E.: Data Mining: Practical Machine Learning Tools and Techniques, 2nd edn. Morgan Kaufmann, San Francisco (2005)","edition":"2"},{"key":"45_CR40","doi-asserted-by":"crossref","unstructured":"Dasgupta, S.: Performance guarantees for hierarchical clustering. In: 15th Annual Conference on Computational Learning Theory, pp. 351\u2013363 (2002)","DOI":"10.1007\/3-540-45435-7_24"}],"container-title":["Progress in Artificial Intelligence"],"original-title":[],"language":"en","link":[{"URL":"http:\/\/link.springer.com\/content\/pdf\/10.1007\/s13748-014-0045-6.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"text-mining"},{"URL":"http:\/\/link.springer.com\/article\/10.1007\/s13748-014-0045-6\/fulltext.html","content-type":"text\/html","content-version":"vor","intended-application":"text-mining"},{"URL":"http:\/\/link.springer.com\/content\/pdf\/10.1007\/s13748-014-0045-6","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,5,2]],"date-time":"2025-05-02T09:03:41Z","timestamp":1746176621000},"score":1,"resource":{"primary":{"URL":"http:\/\/link.springer.com\/10.1007\/s13748-014-0045-6"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2014,4,8]]},"references-count":40,"journal-issue":{"issue":"1","published-print":{"date-parts":[[2014,8]]}},"alternative-id":["45"],"URL":"https:\/\/doi.org\/10.1007\/s13748-014-0045-6","relation":{},"ISSN":["2192-6352","2192-6360"],"issn-type":[{"value":"2192-6352","type":"print"},{"value":"2192-6360","type":"electronic"}],"subject":[],"published":{"date-parts":[[2014,4,8]]}}}