{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,3,15]],"date-time":"2026-03-15T23:24:01Z","timestamp":1773617041957,"version":"3.50.1"},"reference-count":18,"publisher":"Pleiades Publishing Ltd","issue":"3","license":[{"start":{"date-parts":[[2019,3,1]],"date-time":"2019-03-01T00:00:00Z","timestamp":1551398400000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/www.springernature.com\/gp\/researchers\/text-and-data-mining"},{"start":{"date-parts":[[2019,3,1]],"date-time":"2019-03-01T00:00:00Z","timestamp":1551398400000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/www.springernature.com\/gp\/researchers\/text-and-data-mining"}],"content-domain":{"domain":["link.springer.com"],"crossmark-restriction":false},"short-container-title":["Autom Remote Control"],"published-print":{"date-parts":[[2019,3]]},"DOI":"10.1134\/s0005117919030093","type":"journal-article","created":{"date-parts":[[2019,4,24]],"date-time":"2019-04-24T01:51:54Z","timestamp":1556070714000},"page":"502-512","update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":3,"title":["Entropy-Based Estimation in Classification Problems"],"prefix":"10.1134","volume":"80","author":[{"given":"Yu. A.","family":"Dubnov","sequence":"first","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"137","published-online":{"date-parts":[[2019,4,24]]},"reference":[{"key":"946_CR1","volume-title":"Pattern Recognition and Machine Learning (Information Science and Statistics)","author":"C. Bishop","year":"2006","unstructured":"Bishop, C., Pattern Recognition and Machine Learning (Information Science and Statistics), New York: Springer, 2006."},{"key":"946_CR2","volume-title":"Classification and Regression Trees, Monterey: Wadsworth & Brooks\/Cole Advanced Books & Software","author":"L. Breiman","year":"1984","unstructured":"Breiman, L., Friedman, J.H., Olshen, R.A., and Stone, C.J., Classification and Regression Trees, Monterey: Wadsworth & Brooks\/Cole Advanced Books & Software, 1984."},{"key":"946_CR3","doi-asserted-by":"publisher","first-page":"103","DOI":"10.1023\/A:1007413511361","volume":"29","author":"P. Domingos","year":"1997","unstructured":"Domingos, P. and Pazzani, M., On the Optimality of the Simple Bayesian Classifier under Zero-One Loss, Mach. Learn., 1997, no. 29, pp. 103\u2013130.","journal-title":"Mach. Learn."},{"key":"946_CR4","volume-title":"Applied Logistic Regression","author":"D.W. Hosmer","year":"2002","unstructured":"Hosmer, D.W. and Lemeshow, S., Applied Logistic Regression, New York: Chichester, 2002, 2nd ed."},{"key":"946_CR5","volume-title":"Ed., Nearest Neighbor (NN) Norms: NN Pattern Classification Techniques","author":"B.V. Dasarathy","year":"1991","unstructured":"Dasarathy, B.V., Ed., Nearest Neighbor (NN) Norms: NN Pattern Classification Techniques, Los Alamitos: IEEE Computer Society Press 1991."},{"key":"946_CR6","doi-asserted-by":"publisher","DOI":"10.1017\/CBO9780511801389","volume-title":"An Introduction to Support Vector Machines and Other Kernel- Based Learning Methods","author":"N. Cristianini","year":"2000","unstructured":"Cristianini, N. and Shawe-Taylor, J., An Introduction to Support Vector Machines and Other Kernel- Based Learning Methods, Cambridge: Cambridge Univ. Press, 2000."},{"key":"946_CR7","volume-title":"Boosting Algorithms: Regularization, Prediction and Model Fiting, Stat. Sci.","author":"P. B\u00fchlmann","year":"2007","unstructured":"B\u00fchlmann, P. and Hothorn, T., Boosting Algorithms: Regularization, Prediction and Model Fiting, Stat. Sci., 2007, pp. 477\u2013505."},{"key":"946_CR8","doi-asserted-by":"publisher","DOI":"10.1002\/0471200611","volume-title":"Elements of Information Theory","author":"T.M. Cover","year":"1991","unstructured":"Cover, T.M. and Thomas, J.A., Elements of Information Theory, New York: Wiley, 1991."},{"issue":"6","key":"946_CR9","doi-asserted-by":"publisher","first-page":"247","DOI":"10.3390\/e19060247","volume":"19","author":"J. Abell\u00e1n","year":"2017","unstructured":"Abell\u00e1n, J. and Castellano, J.G., Improving the Naive Bayes Classifier via a Quick Variable Selection Method Using Maximum of Entropy, Entropy, 2017, vol. 19, no. 6, p. 247.","journal-title":"Entropy"},{"key":"946_CR10","first-page":"108","volume":"3","author":"S.J. Phillips","year":"2009","unstructured":"Phillips, S.J., A Brief Tutorial on Maxent. Network of Conservation Educators and Practitioners, Center for Biodiversity and Conservation, American Museum of Natural History, Lessons in Conservation, 2009, vol. 3, pp. 108\u2013135.","journal-title":"Center for Biodiversity and Conservation, American Museum of Natural History, Lessons in Conservation"},{"key":"946_CR11","doi-asserted-by":"publisher","first-page":"41","DOI":"10.1007\/s10994-010-5221-8","volume":"85","author":"H.-F. Yu","year":"2011","unstructured":"Yu, H.-F., Huang, F.-L., and Lin, C.-J., Dual Coordinate Descent Methods for Logistic Regression and Maximum Entropy Models, Mach. Lear., 2011, vol. 85, pp. 41\u201375.","journal-title":"Mach. Lear."},{"key":"946_CR12","volume-title":"Maximum Entropy Econometrics: Robust Estimation with Limited Data","author":"A. Golan","year":"1996","unstructured":"Golan, A., Judge, G.G., and Miller, D., Maximum Entropy Econometrics: Robust Estimation with Limited Data, Chichester: Wiley, 1996."},{"key":"946_CR13","volume-title":"Generalized Maximum Entropy (GME) Estimator: Formulation and a Monte Carlo Study, VII National Sympos. on Econometrics and Statistics","author":"H.O. Eruygur","year":"2005","unstructured":"Eruygur, H.O., Generalized Maximum Entropy (GME) Estimator: Formulation and a Monte Carlo Study, VII National Sympos. on Econometrics and Statistics, Istanbul, Turkey, 2005, May 26\u201327."},{"key":"946_CR14","volume-title":"Randomized Machine Learning: Statement, Solution, Applications, Proc. 2016IEEE 8-th Int. Conf. on Intelligent Systems (IS16), September 4\u20136","author":"Yu.S. Popkov","year":"2016","unstructured":"Popkov, Yu.S., Dubnov, Yu.A., and Popkov, A.Yu., Randomized Machine Learning: Statement, Solution, Applications, Proc. 2016IEEE 8-th Int. Conf. on Intelligent Systems (IS16), September 4\u20136, 2016, Sofia, Bulgaria, pp. 27\u201339."},{"key":"946_CR15","first-page":"273","volume":"6","author":"J. Langford","year":"2005","unstructured":"Langford, J., Tutorial on Practical Prediction Theory for Classification, J. Mach. Learn. Research, 2005, vol. 6, pp. 273\u2013306.","journal-title":"J. Mach. Learn. Research"},{"key":"946_CR16","volume-title":"Entropy","author":"Yu.S. Popkov","year":"2017","unstructured":"Popkov, Yu.S., Volkovich, Z., Dubnov, Yu.A., Avros, R., and Ravve, E., Entropy \u20182\u2019-Soft Classification of Objects, Entropy, 2017, vol. 19, no. 4, no. 178."},{"key":"946_CR17","doi-asserted-by":"publisher","first-page":"861","DOI":"10.1016\/j.patrec.2005.10.010","volume":"27","author":"T. Fawcett","year":"2006","unstructured":"Fawcett, T., An Introduction to ROC Analysis, Pattern Recogn. Lett., 2006, no. 27, pp. 861\u2013874.","journal-title":"Pattern Recogn. Lett."},{"key":"946_CR18","volume-title":"J. Multiple-Valued Logic Soft Computing","author":"J. Alcal\u00e1-Fdez","year":"2011","unstructured":"Alcal\u00e1-Fdez, J., Fernandez, A., Luengo, J., Derrac, J., Garcia, S., S\u00e1nchez, L., and Herrera, F., KEEL Data-Mining Software Tool: Data Set Repository, Integration of Algorithms and Experimental Analysis Framework, J. Multiple-Valued Logic Soft Computing, 2011, vol. 17, no. 2\u20133, pp. 255\u2013287."}],"container-title":["Automation and Remote Control"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1134\/S0005117919030093.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/link.springer.com\/article\/10.1134\/S0005117919030093","content-type":"text\/html","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1134\/S0005117919030093.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2026,3,15]],"date-time":"2026-03-15T22:32:37Z","timestamp":1773613957000},"score":1,"resource":{"primary":{"URL":"https:\/\/link.springer.com\/10.1134\/S0005117919030093"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2019,3]]},"references-count":18,"journal-issue":{"issue":"3","published-print":{"date-parts":[[2019,3]]}},"alternative-id":["946"],"URL":"https:\/\/doi.org\/10.1134\/s0005117919030093","relation":{},"ISSN":["0005-1179","1608-3032"],"issn-type":[{"value":"0005-1179","type":"print"},{"value":"1608-3032","type":"electronic"}],"subject":[],"published":{"date-parts":[[2019,3]]},"assertion":[{"value":"19 July 2017","order":1,"name":"received","label":"Received","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"6 November 2018","order":2,"name":"revised","label":"Revised","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"8 November 2018","order":3,"name":"accepted","label":"Accepted","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"24 April 2019","order":4,"name":"first_online","label":"First Online","group":{"name":"ArticleHistory","label":"Article History"}}]}}