{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,2,19]],"date-time":"2026-02-19T02:14:11Z","timestamp":1771467251094,"version":"3.50.1"},"reference-count":70,"publisher":"Springer Science and Business Media LLC","issue":"2","license":[{"start":{"date-parts":[[2017,2,6]],"date-time":"2017-02-06T00:00:00Z","timestamp":1486339200000},"content-version":"unspecified","delay-in-days":0,"URL":"http:\/\/www.springer.com\/tdm"}],"content-domain":{"domain":["link.springer.com"],"crossmark-restriction":false},"short-container-title":["Prog Artif Intell"],"published-print":{"date-parts":[[2017,6]]},"DOI":"10.1007\/s13748-017-0114-8","type":"journal-article","created":{"date-parts":[[2017,2,6]],"date-time":"2017-02-06T20:19:48Z","timestamp":1486412388000},"page":"87-104","update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":9,"title":["Preserving output-privacy in data stream classification"],"prefix":"10.1007","volume":"6","author":[{"given":"Radhika","family":"Kotecha","sequence":"first","affiliation":[]},{"given":"Sanjay","family":"Garg","sequence":"additional","affiliation":[]}],"member":"297","published-online":{"date-parts":[[2017,2,6]]},"reference":[{"key":"114_CR1","doi-asserted-by":"publisher","unstructured":"Agarwal, R., Srikant R.: Privacy-preserving data mining. In: Proceedings of the 2000 ACM SIGMOD International Conference on Management of Data, pp. 439\u2013450 (2000)","DOI":"10.1145\/342009.335438"},{"key":"114_CR2","doi-asserted-by":"publisher","unstructured":"Lindell, Y., Pinkas, B.: Privacy preserving data mining. In: Proceedings of 20th Annual International Cryptology Conference on Advances in Cryptology. Springer, pp. 36\u201354 (2000)","DOI":"10.1007\/3-540-44598-6_3"},{"key":"114_CR3","doi-asserted-by":"publisher","first-page":"313","DOI":"10.1007\/978-0-387-70992-5_13","volume-title":"Privacy-Preserving Data Mining: Models and Algorithms, vol. 34 of Advances in Database Systems","author":"M Kantarcioglu","year":"2008","unstructured":"Kantarcioglu, M.: A survey of privacy-preserving methods across horizontally partitioned data. In: Aggarwal, C., Yu, P. (eds.) Privacy-Preserving Data Mining: Models and Algorithms, vol. 34 of Advances in Database Systems, pp. 313\u2013336. Springer, Berlin (2008)"},{"key":"114_CR4","doi-asserted-by":"publisher","unstructured":"Zhang, N., Wang, S., Zhao, W.: A new scheme on privacy-preserving data classification. In: Proceedings of ACM International Conference on Knowledge Discovery and Data Mining, pp. 374\u2013383 (2005)","DOI":"10.1145\/1081870.1081913"},{"issue":"6","key":"114_CR5","doi-asserted-by":"publisher","first-page":"1010","DOI":"10.1109\/69.971193","volume":"13","author":"P Samarati","year":"2001","unstructured":"Samarati, P.: Protecting respondents\u2019 identities in microdata release. IEEE Trans. Knowl. Eng. 13(6), 1010\u20131027 (2001)","journal-title":"IEEE Trans. Knowl. Eng."},{"issue":"5","key":"114_CR6","doi-asserted-by":"publisher","first-page":"711","DOI":"10.1109\/TKDE.2007.1015","volume":"19","author":"BCM Fung","year":"2007","unstructured":"Fung, B.C.M., Wang, K., Yu, P.: Anonymizing classification data for privacy preservation. IEEE Trans. Knowl. Data Eng. 19(5), 711\u2013725 (2007)","journal-title":"IEEE Trans. Knowl. Data Eng."},{"issue":"1","key":"114_CR7","doi-asserted-by":"publisher","first-page":"1","DOI":"10.1145\/1929934.1929935","volume":"36","author":"T Wang","year":"2011","unstructured":"Wang, T., Liu, L.: Output privacy in data mining. ACM Trans. Database Syst. 36(1), 1\u201334 (2011)","journal-title":"ACM Trans. Database Syst."},{"issue":"4","key":"114_CR8","doi-asserted-by":"publisher","first-page":"789","DOI":"10.1007\/s00778-006-0039-5","volume":"17","author":"A Friedman","year":"2008","unstructured":"Friedman, A., Wolff, R., Schuster, A.: Providing k-anonymity in data mining. Int. J. Very Large Data Bases 17(4), 789\u2013804 (2008)","journal-title":"Int. J. Very Large Data Bases"},{"key":"114_CR9","doi-asserted-by":"crossref","unstructured":"Hwanjo, Y., Xiaoqian, J., Vaidya J.: Privacy-preserving SVM using nonlinear kernels on horizontally partitioned data. In: Proceedings of ACM SAC International Conference, pp. 603\u2013610 (2006)","DOI":"10.1145\/1141277.1141415"},{"issue":"2","key":"114_CR10","doi-asserted-by":"publisher","first-page":"12","DOI":"10.1145\/772862.772865","volume":"4","author":"B Pinkas","year":"2002","unstructured":"Pinkas, B.: Cryptographic techniques for privacy-preserving data mining. ACM SIGKDD Explor. 4(2), 12\u201319 (2002)","journal-title":"ACM SIGKDD Explor."},{"key":"114_CR11","doi-asserted-by":"publisher","unstructured":"Kantarcioglu, M., Jin, J., Clifton, C.: When do data mining results violate privacy? In: Proceedings of International Conference on Knowledge Discovery and Data Mining, pp. 599\u2013604 (2004)","DOI":"10.1145\/1014052.1014126"},{"key":"114_CR12","unstructured":"Samarati, P., Sweeney, L.: Protecting privacy when disclosing information: k-anonymity and its enforcement through generalization and suppression. In: IEEE Symposium on Research in Security and Privacy, pp. 188\u2013206 (1998)"},{"key":"114_CR13","doi-asserted-by":"publisher","unstructured":"Samet, S., Miri A.: Privacy preserving ID3 using Gini index over horizontally partitioned data. In: Computer Systems and Applications, pp. 645\u2013651 (2008)","DOI":"10.1109\/AICCSA.2008.4493598"},{"key":"114_CR14","doi-asserted-by":"publisher","unstructured":"Emekci, F., Sahin, O., Agrawal, D., Abbadi, A.: Privacy preserving decision tree learning over multiple parties. In: Data and Knowledge Engineering, pp. 348\u2013361 (2007)","DOI":"10.1016\/j.datak.2007.02.004"},{"key":"114_CR15","doi-asserted-by":"publisher","unstructured":"Dwork, C.: Differential privacy. In: International Colloquium on Automata, Languages and Programming, pp. 1\u201312 (2006)","DOI":"10.1007\/11787006_1"},{"key":"114_CR16","doi-asserted-by":"publisher","unstructured":"Xiong, L., Chitti, S., Liu L.: Mining multiple private databases using a kNN classifier. In: Proceedings of ACM SAC International Conference, pp. 435\u2013440 (2007)","DOI":"10.1145\/1244002.1244102"},{"key":"114_CR17","doi-asserted-by":"publisher","first-page":"879","DOI":"10.1007\/s00778-006-0041-y","volume":"17","author":"J Vaidya","year":"2007","unstructured":"Vaidya, J., Kantarcioglu, M., Clifton, C.: Privacy-preserving Na\u00efve Bayes classification. Int. J. Very Large Data Bases 17, 879\u2013898 (2007)","journal-title":"Int. J. Very Large Data Bases"},{"key":"114_CR18","volume-title":"Data Streams Models and Algorithms. Advances in Database Systems","author":"C Aggarwal","year":"2006","unstructured":"Aggarwal, C.: Data Streams Models and Algorithms. Advances in Database Systems. Springer, Berlin (2006)"},{"key":"114_CR19","unstructured":"Bifet, A., Holmes, G., Kirkby, R., Pfahringer, B.: Data stream mining\u2014a practical approach. Technical report, Department of Computer Science, San University of Waikato, New Zealand (2011)"},{"key":"114_CR20","doi-asserted-by":"crossref","DOI":"10.1007\/978-3-031-01837-4","volume-title":"Data Stream Management","author":"L Golab","year":"2010","unstructured":"Golab, L., Ozsu, T.: Data Stream Management. Morgan and Claypool Publishers, San Mateo (2010)"},{"issue":"1","key":"114_CR21","doi-asserted-by":"publisher","first-page":"22","DOI":"10.1109\/TKDE.2010.36","volume":"23","author":"H Abdulsalam","year":"2011","unstructured":"Abdulsalam, H., Skillicorn, D., Martin, P.: Classification using streaming random forests. IEEE Trans. Knowl. Data Eng. 23(1), 22\u201336 (2011)","journal-title":"IEEE Trans. Knowl. Data Eng."},{"key":"114_CR22","doi-asserted-by":"publisher","unstructured":"Aggarwal, C.: On abnormality detection in spuriously populated data streams. In: Proceedings of SIAM Conference on Data Mining (2005)","DOI":"10.1137\/1.9781611972757.8"},{"key":"114_CR23","doi-asserted-by":"publisher","unstructured":"Kotecha, R., Garg, S.: Data Streams and privacy: two emerging issues in data classification. In: Proceedings of 5th Nirma University International Conference on Engineering, IEEE (2015)","DOI":"10.1109\/NUICONE.2015.7449597"},{"key":"114_CR24","doi-asserted-by":"publisher","first-page":"847","DOI":"10.1016\/j.eswa.2006.07.007","volume":"37","author":"C Huang","year":"2007","unstructured":"Huang, C., Chen, M., Wang, C.: Credit scoring with a data mining approach based on support vector machines. Expert Syst. Appl. 37, 847\u2013856 (2007)","journal-title":"Expert Syst. Appl."},{"key":"114_CR25","doi-asserted-by":"publisher","first-page":"1113","DOI":"10.1016\/j.csda.2004.11.006","volume":"50","author":"T Lee","year":"2006","unstructured":"Lee, T., Chiu, C., Chou, Y., Lu, C.: Mining the customer credit using classification and regression tree and multivariate adaptive regression splines. Comput. Stat. Data Anal. 50, 1113\u20131130 (2006)","journal-title":"Comput. Stat. Data Anal."},{"key":"114_CR26","doi-asserted-by":"publisher","first-page":"1","DOI":"10.1016\/j.ejor.2015.05.030","volume":"247","author":"S Lessmann","year":"2015","unstructured":"Lessmann, S., Baesens, B., Seow, H., Thomas, L.: Benchmarking state-of-the-art classification algorithms for credit scoring: an update of research. Eur. J. Oper. Res. 247, 1\u201332 (2015)","journal-title":"Eur. J. Oper. Res."},{"key":"114_CR27","doi-asserted-by":"publisher","first-page":"3326","DOI":"10.1016\/j.eswa.2009.10.018","volume":"37","author":"B Twala","year":"2010","unstructured":"Twala, B.: Multiple classifier application to credit risk assessment. Expert Syst. Appl. 37, 3326\u20133336 (2010)","journal-title":"Expert Syst. Appl."},{"key":"114_CR28","doi-asserted-by":"publisher","first-page":"61","DOI":"10.1016\/j.knosys.2011.06.020","volume":"26","author":"G Wang","year":"2012","unstructured":"Wang, G., Mac, J., Huang, L., Xu, K.: Two credit scoring models based on dual strategy ensemble trees. Knowl. Based Syst. 26, 61\u201368 (2012)","journal-title":"Knowl. Based Syst."},{"key":"114_CR29","doi-asserted-by":"publisher","first-page":"2473","DOI":"10.1016\/j.eswa.2007.12.020","volume":"36","author":"I Yeh","year":"2009","unstructured":"Yeh, I., Lien, C.: The comparisons of data mining techniques for the predictive accuracy of probability of default of credit card clients. Expert Syst. Appl. 36, 2473\u20132480 (2009)","journal-title":"Expert Syst. Appl."},{"key":"114_CR30","doi-asserted-by":"publisher","first-page":"1434","DOI":"10.1016\/j.eswa.2007.01.009","volume":"34","author":"L Yu","year":"2008","unstructured":"Yu, L., Wang, S., Lai, K.: Credit risk assessment with a multistage neural network ensemble learning approach. Expert Syst. Appl. 34, 1434\u20131444 (2008)","journal-title":"Expert Syst. Appl."},{"key":"114_CR31","doi-asserted-by":"publisher","unstructured":"Domingos, P., Hulten, G.: Mining high-speed data streams. In: Proceedings of 6th ACM International Conference on Knowledge Discovery and Data Mining (2000)","DOI":"10.1145\/347090.347107"},{"key":"114_CR32","doi-asserted-by":"publisher","unstructured":"Hulten, G., Spencer, L., Domingos, P.: Mining time-changing data streams. In: Proceedings of ACM International Conference on Knowledge Discovery and Data Mining (2001)","DOI":"10.1145\/502512.502529"},{"key":"114_CR33","doi-asserted-by":"publisher","first-page":"577","DOI":"10.1109\/TKDE.2006.69","volume":"18","author":"C Aggarwal","year":"2006","unstructured":"Aggarwal, C., Han, J., Wang, J., Yu, P.: A framework for on-demand classification of evolving data streams. IEEE Trans. Knowl. Data Eng. 18, 577\u2013589 (2006)","journal-title":"IEEE Trans. Knowl. Data Eng."},{"issue":"15","key":"114_CR34","doi-asserted-by":"publisher","first-page":"5895","DOI":"10.1016\/j.eswa.2013.05.001","volume":"40","author":"D Farid","year":"2013","unstructured":"Farid, D., Zhang, L., Hossain, A., Rahman, C., Strachan, R., Sexton, G., Dahal, K.: An adaptive ensemble classifier for mining concept drifting data streams. Expert Syst. Appl. 40(15), 5895\u20135906 (2013)","journal-title":"Expert Syst. Appl."},{"key":"114_CR35","doi-asserted-by":"crossref","unstructured":"Bifet, A., Gavalda R.: Adaptive parameter-free learning from evolving data streams. Technical report, Polytechnic University of Catalonia (2009)","DOI":"10.1007\/978-3-642-03915-7_22"},{"key":"114_CR36","doi-asserted-by":"publisher","unstructured":"Wang, H., Fan, W., Yu, P., Han J.: Mining concept-drifting data streams using ensemble classifiers. In: Proceedings of 9th ACM International Conference on Knowledge Discovery and Data Mining (2003)","DOI":"10.1145\/956750.956778"},{"key":"114_CR37","doi-asserted-by":"publisher","first-page":"859","DOI":"10.1109\/TKDE.2010.61","volume":"23","author":"M Masud","year":"2011","unstructured":"Masud, M., Gao, J., Khan, L., Han, J., Thuraisingham, B.: Classification and novel class detection in concept-drifting data streams under time constraints. IEEE Trans. Knowl. Data Eng. 23, 859\u2013874 (2011)","journal-title":"IEEE Trans. Knowl. Data Eng."},{"key":"114_CR38","doi-asserted-by":"crossref","unstructured":"Godase, A., Attar, V.: Classifier ensemble for imbalanced data stream classification. In: Proceedings of ACM CUBE International Information Technology Conference (2012)","DOI":"10.1145\/2381716.2381769"},{"key":"114_CR39","first-page":"337","volume":"7","author":"V Ayala-Rivera","year":"2014","unstructured":"Ayala-Rivera, V., McDonagh, P., Cerqueus, T., Murphy, L.: A systematic comparison and evaluation of k-anonymization algorithms for practitioners. Trans. Data Priv. 7, 337\u2013370 (2014)","journal-title":"Trans. Data Priv."},{"key":"114_CR40","first-page":"1","volume":"8","author":"G Aggarwal","year":"2005","unstructured":"Aggarwal, G., Feder, T., Kenthapadi, K., Motwani, R., Panigrahy, R., Thomas, D., Zhu, A.: Approximation algorithms for k-anonymity. J. Privacy Technol. 8, 1\u201318 (2005)","journal-title":"J. Privacy Technol."},{"key":"114_CR41","doi-asserted-by":"publisher","unstructured":"Bayardo, R., Agrawal, R.: Data privacy through optimal k-anonymization. In: Proceedings of 21st International Conference on Data Engineering, pp. 217\u2013228 (2005)","DOI":"10.1109\/ICDE.2005.42"},{"key":"114_CR42","doi-asserted-by":"publisher","unstructured":"Bertino, E., Ooi, C., Yang, Y., Deng, R.: Privacy and ownership preserving of outsourced medical data. In: Proceedings of 21st International Conference on Data Engineering, pp. 521\u2013532 (2005)","DOI":"10.1109\/ICDE.2005.111"},{"key":"114_CR43","doi-asserted-by":"publisher","unstructured":"Fung, B., Wang, K., Yu, P.: Top-Down Specialization for Information and Privacy Preservation. In: Proceedings of 21st International Conference on Data Engineering, pp. 205\u2013216 (2005)","DOI":"10.1109\/ICDE.2005.143"},{"key":"114_CR44","doi-asserted-by":"publisher","unstructured":"Iyengar, V.: Transforming data to satisfy privacy constraints. In: Proceedings of the 8th ACM SIGKDD International Conference on Knowledge discovery and Data Mining, pp. 279\u2013288 (2002)","DOI":"10.1145\/775047.775089"},{"key":"114_CR45","doi-asserted-by":"publisher","unstructured":"LeFevre, K., DeWitt, D., Ramakrishnan, R.: Mondrian multidimensional k-anonymity. In: Proceedings of 22nd International Conference on Data Engineering (2006)","DOI":"10.1109\/ICDE.2006.101"},{"issue":"1","key":"114_CR46","doi-asserted-by":"publisher","first-page":"45","DOI":"10.1145\/1217299.1217302","volume":"1","author":"A Machanavajjhala","year":"2007","unstructured":"Machanavajjhala, A., Kifer, D., Gehrke, J., Venkitasubramaniam, M.: l-diversity: Privacy beyond k-anonymity. ACM Trans. Knowl. Discov. Data 1(1), 45\u201396 (2007)","journal-title":"ACM Trans. Knowl. Discov. Data"},{"key":"114_CR47","first-page":"53","volume":"1","author":"X Sun","year":"2008","unstructured":"Sun, X., Wang, H., Li, J., Truta, T.M.: Enhanced p-sensitive k-anonymity models for privacy preserving data publishing. Trans. Data Priv. 1, 53\u201366 (2008)","journal-title":"Trans. Data Priv."},{"key":"114_CR48","first-page":"433","volume":"5","author":"H Tian","year":"2012","unstructured":"Tian, H., Zhang, W., Xu, S., Sharkey, P.: A knowledge model sharing based approach to privacy-preserving data mining. Trans. Data Priv. 5, 433\u2013467 (2012)","journal-title":"Trans. Data Priv."},{"key":"114_CR49","doi-asserted-by":"publisher","unstructured":"Sweeney, L.: k-Anonymity: a model for protecting privacy. Int. J. Uncertain. Fuzziness Knowl. Based Syst. 10(5), 557\u2013570 (2002)","DOI":"10.1142\/S0218488502001648"},{"key":"114_CR50","doi-asserted-by":"publisher","unstructured":"Li, N., Li, T.: t-Closeness: privacy beyond k-anonymity and l-diversity. In: Proceedings of the 23rd International Conference on Data Engineering, pp. 106\u2013115 (2007)","DOI":"10.1109\/ICDE.2007.367856"},{"key":"114_CR51","doi-asserted-by":"publisher","unstructured":"Wang, K., Yu, P., Chakraborty, S.: Bottom-up generalization: a data mining solution to privacy protection. In: Proceedings of 4th IEEE International Conference on Data Mining (2004)","DOI":"10.1109\/ICDM.2004.10110"},{"key":"114_CR52","doi-asserted-by":"publisher","first-page":"13","DOI":"10.1080\/01621459.1963.10500830","volume":"58","author":"W Hoeffding","year":"1963","unstructured":"Hoeffding, W.: Probability inequalities for sums of bounded random variables. J. Am. Stat. Assoc. 58, 13\u201330 (1963)","journal-title":"J. Am. Stat. Assoc."},{"key":"114_CR53","unstructured":"Kirkby, R.: Improving Hoeffding Trees. Ph.D. thesis, Department of Computer Science, University of Waikato (2007)"},{"key":"114_CR54","doi-asserted-by":"publisher","unstructured":"Xiao, X., Tao, Y.: M-invariance: towards privacy preserving re-publication of dynamic datasets. In: Proceedings of the 2007 ACM SIGMOD International Conference on Management of Data, pp. 689\u2013700 (2007)","DOI":"10.1145\/1247480.1247556"},{"key":"114_CR55","doi-asserted-by":"publisher","unstructured":"Pei, J., Xu, J., Wang, Z., Wang, W., Wang, K.: Maintaining k-anonymity against incremental updates. In: Proceedings of the 19th International Conference on Scientific and Statistical Database Management. IEEE (2007)","DOI":"10.1109\/SSDBM.2007.16"},{"key":"114_CR56","doi-asserted-by":"publisher","unstructured":"Fung, B.C.M., Wang, K., Fu, A.W.C., Pei, J.: Anonymity for continuous data publishing. In: Proceedings of the 11th International Conference on Extending Database Technology. ACM (2008)","DOI":"10.1145\/1353343.1353378"},{"key":"114_CR57","doi-asserted-by":"publisher","unstructured":"Li, J., Ooi, B.C., Wang, W.: Anonymizing streaming data for privacy protection. In: Proceedings of the 24th International Conference on Data Engineering, pp. 1367\u20131369. IEEE (2008)","DOI":"10.1109\/ICDE.2008.4497558"},{"key":"114_CR58","doi-asserted-by":"crossref","unstructured":"Cao, J., Carminati, B., Ferrari, E., Tan, K.L.: CASTLE: a delay-constrained scheme for ks-anonymizing data streams. In: Proceedings of the 24th International Conference on Data Engineering, pp. 1376\u20131378. IEEE (2008)","DOI":"10.1109\/ICDE.2008.4497561"},{"key":"114_CR59","doi-asserted-by":"publisher","unstructured":"Zhou, B., Han, Y., Pei, J., Jiang, B., Tao, Y., Jia, Y.: Continuous privacy preserving publishing of data streams. In: Proceedings of the 12th International Conference on Extending Database Technology: Advances in Database Technology, pp. 648\u2013659 (2009)","DOI":"10.1145\/1516360.1516435"},{"issue":"3","key":"114_CR60","first-page":"321","volume":"12","author":"C Chao","year":"2009","unstructured":"Chao, C., Chen, P., Sun, C.: Privacy-preserving classification of data streams. Tamkang J. Sci. Eng. 12(3), 321\u2013330 (2009)","journal-title":"Tamkang J. Sci. Eng."},{"key":"114_CR61","doi-asserted-by":"publisher","unstructured":"Chhinkaniwala, H., Garg, S.: Tuple value based multiplicative data perturbation approach to preserve privacy in data stream mining. Int. J. Data Min. Knowl. Manag. Process 3(3), 53\u201361 (2013)","DOI":"10.5121\/ijdkp.2013.3305"},{"key":"114_CR62","unstructured":"Chhinkaniwala, H., Patel, K., Garg, S.: Privacy preserving data stream classification using data perturbation techniques. In: Proceedings of International Conference on Emerging Trends in Electrical, Electronics and Communication Technologies (2012)"},{"key":"114_CR63","doi-asserted-by":"publisher","first-page":"487","DOI":"10.1007\/978-0-387-70992-5_20","volume-title":"Privacy-Preserving Data Mining: Models and Algorithms, vol. 34 of Advances in Database Systems","author":"Y Xu","year":"2008","unstructured":"Xu, Y., Wang, K., Fu, A., She, R., Pei, J.: Privacy-preserving data stream classification. In: Aggarwal, C., Yu, P. (eds.) Privacy-Preserving Data Mining: Models and Algorithms, vol. 34 of Advances in Database Systems, pp. 487\u2013510. Springer, Berlin (2008)"},{"key":"114_CR64","volume-title":"Classification and Regression Trees","author":"L Breiman","year":"1993","unstructured":"Breiman, L., Friedman, J., Olshen, R., Stone, C.: Classification and Regression Trees. Chapman and Hall, Boca Raton (1993)"},{"key":"114_CR65","unstructured":"Lichman, M.: UCI machine learning repository. University of California, Irvine, School of Information and Computer Sciences. (2013) http:\/\/archive.ics.uci.edu\/ml . Accessed 20 Nov 2016"},{"key":"114_CR66","unstructured":"Kaggle: Give Me Some Credit Competition-2011. (2016) https:\/\/www.kaggle.com\/c\/GiveMeSomeCredit . Accessed 06 May 2016"},{"key":"114_CR67","unstructured":"Bifet, A., Holmes, G., Kirkby, R., Pfahringer, B.: MOA: massive online analysis. (2014) http:\/\/moa.cms.waikato.ac.nz"},{"key":"114_CR68","doi-asserted-by":"publisher","unstructured":"Breiman, L.: Bagging predictors. Mach. Learn. 123\u2013140 (1996)","DOI":"10.1007\/BF00058655"},{"key":"114_CR69","unstructured":"Kohavi, R.: A study of cross-validation and bootstrap for accuracy estimation and model selection. In: Proceedings of International Joint Conference on Artificial Intelligence, pp. 1137\u20131145 (1995)"},{"key":"114_CR70","unstructured":"Han, J., Kamber, M., Pei, J.: Data mining: concepts and techniques. In: 3rd ed. San Mateo: The Morgan Kaufmann Series in Data Management Systems (2011)"}],"container-title":["Progress in Artificial Intelligence"],"original-title":[],"language":"en","link":[{"URL":"http:\/\/link.springer.com\/article\/10.1007\/s13748-017-0114-8\/fulltext.html","content-type":"text\/html","content-version":"vor","intended-application":"text-mining"},{"URL":"http:\/\/link.springer.com\/content\/pdf\/10.1007\/s13748-017-0114-8.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"text-mining"},{"URL":"http:\/\/link.springer.com\/content\/pdf\/10.1007\/s13748-017-0114-8.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,6,15]],"date-time":"2025-06-15T02:04:18Z","timestamp":1749953058000},"score":1,"resource":{"primary":{"URL":"http:\/\/link.springer.com\/10.1007\/s13748-017-0114-8"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2017,2,6]]},"references-count":70,"journal-issue":{"issue":"2","published-print":{"date-parts":[[2017,6]]}},"alternative-id":["114"],"URL":"https:\/\/doi.org\/10.1007\/s13748-017-0114-8","relation":{},"ISSN":["2192-6352","2192-6360"],"issn-type":[{"value":"2192-6352","type":"print"},{"value":"2192-6360","type":"electronic"}],"subject":[],"published":{"date-parts":[[2017,2,6]]}}}