{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,7,4]],"date-time":"2026-07-04T10:47:06Z","timestamp":1783162026278,"version":"3.54.6"},"publisher-location":"Singapore","reference-count":37,"publisher":"Springer Singapore","isbn-type":[{"value":"9789811374029","type":"print"},{"value":"9789811374036","type":"electronic"}],"license":[{"start":{"date-parts":[[2019,7,17]],"date-time":"2019-07-17T00:00:00Z","timestamp":1563321600000},"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":[[2020]]},"DOI":"10.1007\/978-981-13-7403-6_11","type":"book-chapter","created":{"date-parts":[[2019,7,16]],"date-time":"2019-07-16T18:03:48Z","timestamp":1563300228000},"page":"99-111","update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":361,"title":["Supervised Classification Algorithms in Machine Learning: A Survey and Review"],"prefix":"10.1007","author":[{"given":"Pratap Chandra","family":"Sen","sequence":"first","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Mahimarnab","family":"Hajra","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Mitadru","family":"Ghosh","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"297","published-online":{"date-parts":[[2019,7,17]]},"reference":[{"issue":"405","key":"11_CR1","doi-asserted-by":"publisher","first-page":"165","DOI":"10.1080\/01621459.1989.10478752","volume":"84","author":"JH Friedman","year":"1989","unstructured":"J.H. Friedman, Regularized discriminant analysis. J. Am. Stat. Assoc. 84(405), 165\u2013175 (1989)","journal-title":"J. Am. Stat. Assoc."},{"key":"11_CR2","doi-asserted-by":"publisher","first-page":"131","DOI":"10.1023\/A:1007465528199","volume":"29","author":"N Friedman","year":"1997","unstructured":"N. Friedman, D. Geiger, M. Goldszmidt, Bayesian network classifiers. Mach. Learn. 29, 131\u2013163 (1997)","journal-title":"Mach. Learn."},{"issue":"1","key":"11_CR3","doi-asserted-by":"publisher","first-page":"95","DOI":"10.1023\/A:1020249912095","volume":"50","author":"N Friedman","year":"2003","unstructured":"N. Friedman, D. Koller, Being Bayesian about network structure: A Bayesian approach to structure discovery in Bayesian networks. Mach. Learn. 50(1), 95\u2013125 (2003)","journal-title":"Mach. Learn."},{"key":"11_CR4","unstructured":"R.G. Cowell, Conditions under which conditional independence and scoring methods lead to identical selection of Bayesian network models, in Proceedings of 17th International Conference on Uncertainty in Artificial Intelligence"},{"issue":"1\u20132","key":"11_CR5","doi-asserted-by":"publisher","first-page":"99","DOI":"10.1016\/S0169-023X(97)00053-0","volume":"25","author":"RL Mantaras De","year":"1998","unstructured":"R.L. De Mantaras, E. Armengol, Machine learning from examples: inductive and lazy methods. Data Knowl. Eng. 25(1\u20132), 99\u2013123 (1998)","journal-title":"Data Knowl. Eng."},{"key":"11_CR6","first-page":"141","volume-title":"Computation, Causation, and Discovery","author":"D Heckerman","year":"1999","unstructured":"D. Heckerman, C. Meek, G. Cooper, A Bayesian approach to causal discovery, in Computation, Causation, and Discovery, ed. by C. Glymour, G. Cooper (MIT Press, Cambridge, 1999), pp. 141\u2013165"},{"issue":"5","key":"11_CR7","doi-asserted-by":"publisher","first-page":"429","DOI":"10.3233\/IDA-2002-6504","volume":"6","author":"N Japkowicz","year":"2002","unstructured":"N. Japkowicz, S. Stephen, The class imbalance problem: a systematic study. Intell. Data Anal. 6(5), 429\u2013449 (2002)","journal-title":"Intell. Data Anal."},{"key":"11_CR8","unstructured":"D.E. Rumelhart, G.E. Hinton, R.J. Williams, Learning internal representations by error propagation, in Parallel Distributed Processing: Explorations in the Microstructure of Cognition, vol. 1, ed. by D.E. Rumelhart, J.L. McClelland et al. (MIT Press, Cambridge, MA), pp. 318\u2013362."},{"issue":"2","key":"11_CR9","doi-asserted-by":"publisher","first-page":"222","DOI":"10.1109\/91.842155","volume":"8","author":"A. Roy","year":"2000","unstructured":"A. Roy, On connectionism, rule extraction, and brain-like learning. IEEE Trans. Fuzzy Syst. 8(2), 222\u2013227; L. Breiman, Bagging predictors. Mach. Learn. 24, 123\u2013140","journal-title":"IEEE Transactions on Fuzzy Systems"},{"key":"11_CR10","unstructured":"I.J. Good, Probability and the Weighing of Evidence (London, Charles Grin)"},{"key":"11_CR11","unstructured":"N.J. Nilsson, Learning Machines (McGraw-Hill, New York)"},{"key":"11_CR12","unstructured":"B. Cestnik, I. Kononenko, I. Bratko, Assistant 86: a knowledge elicitation tool for sophisticated users, in Proceedings of the Second European Working Session on Learning, pp. 31\u201345"},{"key":"11_CR13","unstructured":"B. Cestnik, Estimating probabilities: a crucial task in machine learning, in Proceedings of the European Conference on Artificial Intelligence, pp. 147\u2013149"},{"issue":"1","key":"11_CR14","doi-asserted-by":"publisher","first-page":"21","DOI":"10.1109\/TIT.1967.1053964","volume":"13","author":"T Cover","year":"1967","unstructured":"T. Cover, P. Hart, Nearest neighbor pattern classification. IEEE Trans. Inf. Theor. 13(1), 21\u201327 (1967)","journal-title":"IEEE Trans. Inf. Theor."},{"key":"11_CR15","doi-asserted-by":"publisher","first-page":"115","DOI":"10.1016\/B978-1-55860-377-6.50023-2","volume-title":"Machine Learning Proceedings 1995","author":"William W. Cohen","year":"1995","unstructured":"W. Cohen, Fast effective rule induction, in Proceedings of ICML-95, pp. 115\u2013123"},{"key":"11_CR16","unstructured":"J.M. Kalyan Roy, Image similarity measure using color histogram, color coherence vector, and sobel method. Int. J. Sci. Res. (IJSR) 2(1), 538\u2013543 (2013), India Online ISSN: 23197064"},{"key":"11_CR17","unstructured":"A. Smola, S. Vishwanathan, Introduction to Machine Learning (United Kingdom at the University Press, Cambridge, 2010)"},{"key":"11_CR18","unstructured":"R.G. Cowell, Conditions under which conditional independence and scoring methods lead to identical selection of Bayesian network models, in Proceedings of 17th International Conference on Uncertainty in Artificial Intelligence (2001)"},{"key":"11_CR19","unstructured":"W. Gerstner, Supervised learning for neural networks: a tutorial with JAVA exercises"},{"key":"11_CR20","unstructured":"R. Olshen L. Breiman, J.H. Friedman, \u201cClassification and regression\u00a0 trees.\u201d\u00a0 Belmont CA Wadsworth International group, \u00a0 \u00a01984. B. C. U. P.E.tgoff, \u201cMultivariate decision trees: machine learning,\u201d no. 19, 1995, pp. 45\u201347."},{"key":"11_CR21","unstructured":"T. Dietterich, M. Kearns, Y. Mansour, Applying the weak learning framework to understand and improve C4. 5 (Sanfrancisco, Morgan), pp. 96\u2013104"},{"key":"11_CR22","unstructured":"Kufmann, in Proceeding of the 13th International Conference on Machine Learning (1996)"},{"key":"11_CR23","doi-asserted-by":"crossref","unstructured":"K.M.A. Chai, H.L. Chieu, H.T. Ng, Bayesian online classifiers for text classification and filtering, in Proceedings of the 25th Annual International ACM SIGIR Conference on Research and Development in Information Retrieval (August 2002), pp. 97\u2013104","DOI":"10.1145\/564392.564395"},{"key":"11_CR24","doi-asserted-by":"crossref","unstructured":"T. Elomaa, The biases of decision treepruning strategies (Springer, 1999), Lecture Notes in Computer Science, vol. 1642, pp. 63\u201374","DOI":"10.1007\/3-540-48412-4_6"},{"key":"11_CR25","doi-asserted-by":"publisher","first-page":"275","DOI":"10.1023\/B:MACH.0000015882.38031.85","volume":"54","author":"A Kalousis","year":"2004","unstructured":"A. Kalousis, G. Gama, On data and algorithms: understanding inductive performance. Mach. Learn. 54, 275\u2013312 (2004)","journal-title":"Mach. Learn."},{"key":"11_CR26","doi-asserted-by":"publisher","first-page":"251","DOI":"10.1023\/A:1021713901879","volume":"50","author":"P Brazdil","year":"2003","unstructured":"P. Brazdil, C. Soares, J. Da Costa, ranking learning algorithms: using IBL and meta-learning on accuracy and time results. Mach. Learn. 50, 251\u2013277 (2003)","journal-title":"Mach. Learn."},{"key":"11_CR27","doi-asserted-by":"publisher","first-page":"519","DOI":"10.1080\/713827181","volume":"17","author":"G Batista","year":"2003","unstructured":"G. Batista, M.C. Monard, An analysis of four missing data treatment methods for supervised learning. Appl. Artif. Intell. 17, 519\u2013533 (2003)","journal-title":"Appl. Artif. Intell."},{"issue":"7","key":"11_CR28","doi-asserted-by":"publisher","first-page":"1525","DOI":"10.1162\/089976604323057470","volume":"16","author":"J Basak","year":"2004","unstructured":"J. Basak, R. Kothari, A classification paradigm for distributed vertically partitioned data. Neural Comput. 16(7), 1525\u20131544 (2004)","journal-title":"Neural Comput."},{"issue":"1","key":"11_CR29","doi-asserted-by":"publisher","first-page":"5","DOI":"10.1023\/A:1007335615132","volume":"26","author":"A Blum","year":"1997","unstructured":"A. Blum, Empirical support for winnow and weighted-majority algorithms: results on a calendar scheduling domain. Mach. Learn. 26(1), 5\u201323 (1997)","journal-title":"Mach. Learn."},{"key":"11_CR30","first-page":"83","volume-title":"Lecture Notes in Computer Science","author":"Andrea Bonarini","year":"2000","unstructured":"A. Bonarini, An Introduction to Learning Fuzzy Classifier Systems (2000), Lecture Notes in Computer Science, vol. 1813, pp. 83\u201392"},{"key":"11_CR31","unstructured":"R. Bouckaert, Choosing between two learning algorithms based on calibrated tests, in Proceedings of 20th International Conference on Machine Learning (Morgan Kaufmann, 2003), pp. 51\u201358"},{"key":"11_CR32","first-page":"1089","volume-title":"Lecture Notes in Computer Science","author":"Remco R. Bouckaert","year":"2004","unstructured":"R. Bouckaert, Naive Bayes Classifiers that Perform Well with Continuous Variables (2004), Lecture Notes in Computer Science, vol. 3339, pp. 1089\u20131094"},{"key":"11_CR33","doi-asserted-by":"publisher","first-page":"251","DOI":"10.1023\/A:1021713901879","volume":"50","author":"P Brazdil","year":"2003","unstructured":"P. Brazdil, C. Soares, J. Da Costa, ranking learning algorithms: using IBL and meta-learning on accuracy and time results. Mach. Learn. 50, 251\u2013277 (2003)","journal-title":"Mach. Learn."},{"key":"11_CR34","unstructured":"L. Breiman, J.H. Friedman, R.A. Olshen, C.J. Stone, Classification and Regression Trees (Wadsforth International Group, 1984)"},{"key":"11_CR35","first-page":"123","volume":"24","author":"L Breiman","year":"1996","unstructured":"L. Breiman, Bagging predictors. Mach. Learn. 24, 123\u2013140 (1996)","journal-title":"Mach. Learn."},{"key":"11_CR36","doi-asserted-by":"publisher","first-page":"1","DOI":"10.1017\/S0269888997000015","volume":"12","author":"LA Breslow","year":"1997","unstructured":"L.A. Breslow, D.W. Aha, Simplifying decision trees: a survey. Knowl. Eng. Rev. 12, 1\u201340 (1997)","journal-title":"Knowl. Eng. Rev."},{"key":"11_CR37","doi-asserted-by":"publisher","first-page":"153","DOI":"10.1023\/A:1014043630878","volume":"6","author":"H Brighton","year":"2002","unstructured":"H. Brighton, C. Mellish, Advances in instance selection for instance-based learning algorithms. Data Min. Knowl. Disc. 6, 153\u2013172 (2002)","journal-title":"Data Min. Knowl. Disc."}],"container-title":["Advances in Intelligent Systems and Computing","Emerging Technology in Modelling and Graphics"],"original-title":[],"language":"en","link":[{"URL":"http:\/\/link.springer.com\/content\/pdf\/10.1007\/978-981-13-7403-6_11","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2019,7,16]],"date-time":"2019-07-16T18:13:21Z","timestamp":1563300801000},"score":1,"resource":{"primary":{"URL":"http:\/\/link.springer.com\/10.1007\/978-981-13-7403-6_11"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2019,7,17]]},"ISBN":["9789811374029","9789811374036"],"references-count":37,"URL":"https:\/\/doi.org\/10.1007\/978-981-13-7403-6_11","relation":{},"ISSN":["2194-5357","2194-5365"],"issn-type":[{"value":"2194-5357","type":"print"},{"value":"2194-5365","type":"electronic"}],"subject":[],"published":{"date-parts":[[2019,7,17]]},"assertion":[{"value":"17 July 2019","order":1,"name":"first_online","label":"First Online","group":{"name":"ChapterHistory","label":"Chapter History"}}]}}