{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2022,4,5]],"date-time":"2022-04-05T20:30:36Z","timestamp":1649190636199},"reference-count":33,"publisher":"Springer Science and Business Media LLC","issue":"1","license":[{"start":{"date-parts":[[2009,3,24]],"date-time":"2009-03-24T00:00:00Z","timestamp":1237852800000},"content-version":"tdm","delay-in-days":0,"URL":"http:\/\/www.springer.com\/tdm"}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Stat Methods Appl"],"published-print":{"date-parts":[[2010,3]]},"DOI":"10.1007\/s10260-009-0116-1","type":"journal-article","created":{"date-parts":[[2009,3,23]],"date-time":"2009-03-23T08:00:10Z","timestamp":1237795210000},"page":"127-139","source":"Crossref","is-referenced-by-count":2,"title":["On using Bayesian networks for complexity reduction in decision trees"],"prefix":"10.1007","volume":"19","author":[{"given":"Adriana","family":"Brogini","sequence":"first","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Debora","family":"Slanzi","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"297","published-online":{"date-parts":[[2009,3,24]]},"reference":[{"key":"116_CR1","doi-asserted-by":"crossref","first-page":"445","DOI":"10.1613\/jair.1061","volume":"18","author":"S Acid","year":"2003","unstructured":"Acid S, de Campos L (2003) Searching for Bayesian network structures in the space of restricted acyclic partially directed graphs. J Artif Intell Res 18: 445\u2013490","journal-title":"J Artif Intell Res"},{"key":"116_CR2","unstructured":"Aliferis CF, Tsamardinos I, Statnikov A (2003) HITON: a novel Markov Blanket\u00a0algorithm for optimal variable selection. In: Proceedings of the 2003 American Medical Informatics Association (AMIA) annual symposium, pp 21\u201325"},{"key":"116_CR3","unstructured":"Bouckaert RR (1995) Bayesian belief networks: from construction to inference. PhD Thesis, University of Utrecht"},{"key":"116_CR4","volume-title":"Classification and regression trees","author":"L Breiman","year":"1984","unstructured":"Breiman L, Friedman JH, Olshen RA, Stone CJ (1984) Classification and regression trees. Wadsworth International Group, Belmont"},{"issue":"1","key":"116_CR5","doi-asserted-by":"crossref","first-page":"1","DOI":"10.1017\/S0269888997000015","volume":"12","author":"LA Breslow","year":"1997","unstructured":"Breslow LA, Aha DW (1997) Simplifying decision trees: a survey. Knowl Eng Rev 12(1): 1\u201340","journal-title":"Knowl Eng Rev"},{"key":"116_CR6","doi-asserted-by":"crossref","unstructured":"Buntine W (1991) Theory refinement on Bayesian networks. In: Proceeding of the seventh conference on uncertainty in artificial intelligence, pp 52\u201360","DOI":"10.1016\/B978-1-55860-203-8.50010-3"},{"key":"116_CR7","volume-title":"Learning from data: artificial intelligence and statistics","author":"DM Chickering","year":"1996","unstructured":"Chickering DM (1996) Learning Bayesian networks is NP-complete. In: Fisher D, Lenz HJ (eds) Learning from data: artificial intelligence and statistics. Springer, New York"},{"issue":"3","key":"116_CR8","doi-asserted-by":"crossref","first-page":"462","DOI":"10.1109\/TIT.1968.1054142","volume":"14","author":"CK Chow","year":"1968","unstructured":"Chow CK, Liu CN (1968) Approximating discrete probability distributions with dependence trees. IEEE Trans Inf Theory 14(3): 462\u2013467","journal-title":"IEEE Trans Inf Theory"},{"key":"116_CR9","first-page":"309","volume":"9","author":"G Cooper","year":"1992","unstructured":"Cooper G, Herskovits E (1992) A Bayesian method for the induction of probabilistic networks from data. Mach Learn 9: 309\u2013347","journal-title":"Mach Learn"},{"key":"116_CR10","volume-title":"Probabilistic networks and expert systems","author":"RG Cowell","year":"1999","unstructured":"Cowell RG, Dawid AP, Lauritzen SL, Spiegelhalter DJ (1999) Probabilistic networks and expert systems. Springer, New York"},{"key":"116_CR11","doi-asserted-by":"crossref","unstructured":"Frey L, Fisher D, Tsamardinos I, Aliferis CF, Statnikov A (2003) Identifying Markov Blankets with decision tree induction. In: Proceedings of third IEEE international conference on data mining (ICDM), Melbourne, pp 59\u201366","DOI":"10.1109\/ICDM.2003.1250903"},{"key":"116_CR12","unstructured":"Friedman N, Goldszmidt M (1996) Learning Bayesian networks with local structures. In: Proceedings of the twelfth conference on uncertainty in artificial intelligence, pp 252\u2013262"},{"key":"116_CR13","volume-title":"Computation, causation and discovery","author":"C Glymour","year":"1999","unstructured":"Glymour C, Cooper GF (1999) Computation, causation and discovery. MIT Press, Cambridge"},{"key":"116_CR14","unstructured":"Hartemink AJ, Gifford DK, Jaakkola TS, Young RA (2002) Combining location and expression data for principled discovery of genetic regulatory network models. In: Pacific symposium on biocomputing, pp 437\u2013449"},{"key":"116_CR15","first-page":"197","volume":"20","author":"D Heckerman","year":"1995","unstructured":"Heckerman D, Geiger D, Chickering DM (1995) Learning Bayesian networks: the combinations of knowledge and statistical data. Mach Learn 20: 197\u2013243","journal-title":"Mach Learn"},{"key":"116_CR16","unstructured":"Herskovits E, Cooper GF (1990) Kutato: an entropy-driven system for the construction of probabilistic expert systems from databases. In: Proceedings of the sixth conference on uncertainty in artificial intelligence, pp 54\u201362"},{"key":"116_CR17","unstructured":"Hornik K, Zeileis A, Hothorn T, Buchta C (2007) RWeka: an R Interface to Weka. R package version 0.3-2"},{"key":"116_CR18","doi-asserted-by":"crossref","DOI":"10.1007\/978-1-4757-3502-4","volume-title":"Bayesian networks and decision graphs","author":"FV Jensen","year":"2001","unstructured":"Jensen FV (2001) Bayesian networks and decision graphs. Springer, New York"},{"key":"116_CR19","doi-asserted-by":"crossref","unstructured":"John GH, Kohavi R, Pleger K (1994) Irrelevant features and the subset selection problem. In: Proceedings of the eleventh international machine learning conference, pp 121\u2013129","DOI":"10.1016\/B978-1-55860-335-6.50023-4"},{"issue":"4","key":"116_CR20","doi-asserted-by":"crossref","first-page":"269","DOI":"10.1111\/j.1467-8640.1994.tb00166.x","volume":"10","author":"W Lam","year":"1994","unstructured":"Lam W, Bacchus F (1994) Learning Bayesian belief networks. An approach based on the MDL principle. Comput Intell 10(4): 269\u2013293","journal-title":"Comput Intell"},{"key":"116_CR21","doi-asserted-by":"crossref","unstructured":"Liu H, Motoda H (2008) Computational methods of feature selection. Chapman & Hall\/CRC, Taylor and Francis Group LLC, London","DOI":"10.1201\/9781584888796"},{"key":"116_CR22","unstructured":"Madden MG (2003) The performance of Bayesian network classifiers constructed using different techniques. In: Working notes of the ECML PkDD-03 Workshop, pp 59\u201370"},{"key":"116_CR23","volume-title":"Proceedings of conference on neural information processing systems (NIPS-12)","author":"D Margaritis","year":"1999","unstructured":"Margaritis D, Thrun S (1999) Bayesian network induction via local neighborhoods. In: Solla S, Leen T, M\u00fcller KR (eds) Proceedings of conference on neural information processing systems (NIPS-12). MIT Press, Cambridge"},{"key":"116_CR24","unstructured":"Meek C (1995) Strong completeness and faithfulness in Bayesian networks. In: Proceedings of the eleventh conference on uncertainty in artificial intelligence, pp 403\u2013410"},{"key":"116_CR25","volume-title":"Machine learning","author":"T Mitchell","year":"1997","unstructured":"Mitchell T (1997) Machine learning. Mc Graw-Hill, New York"},{"key":"116_CR26","volume-title":"Probabilistic reasoning in intelligence systems","author":"J Pearl","year":"1988","unstructured":"Pearl J (1988) Probabilistic reasoning in intelligence systems. Morgan Kaufmann, Los Altos"},{"key":"116_CR27","first-page":"81","volume":"1","author":"JR Quinlan","year":"1986","unstructured":"Quinlan JR (1986) Induction of decision trees. Mach Learn 1: 81\u2013106","journal-title":"Mach Learn"},{"key":"116_CR28","volume-title":"C4.5: programs for machine learning","author":"JR Quinlan","year":"1993","unstructured":"Quinlan JR (1993) C4.5: programs for machine learning. Morgan Kaufmann, Los Altos"},{"key":"116_CR29","unstructured":"Ripley B (2007) The tree package. R package version 1.0-26"},{"issue":"19","key":"116_CR30","doi-asserted-by":"crossref","first-page":"2507","DOI":"10.1093\/bioinformatics\/btm344","volume":"23","author":"Y Saeys","year":"2007","unstructured":"Saeys Y, Inza I, Larra\u00f1aga P (2007) A review of feature selection techniques in bioinformatics. Bioinformatics 23(19): 2507\u20132517","journal-title":"Bioinformatics"},{"key":"116_CR31","doi-asserted-by":"crossref","unstructured":"Schauerhuber M, Zeileis A, Meyer D, Hornik K (2008) Benchmarking open-source tree learners in R\/RWeka. Data analysis, machine learning and applications. In: Proceedings of the 31st annual conference of the Gesellschaft f\u00fcr Klassification","DOI":"10.1007\/978-3-540-78246-9_46"},{"key":"116_CR32","unstructured":"Tsamardinos I, Aliferis C, Statnikov A (2003) Algorithms for large scale markov blanket discovery. In: The sixteenth international flairs conference, St. Augustine, USA"},{"key":"116_CR33","volume-title":"Data mining: practical machine learning tools and techniques","author":"I Witten","year":"2005","unstructured":"Witten I, Frank E (2005) Data mining: practical machine learning tools and techniques, 2nd edn. Morgan Kaufmann, San Francisco","edition":"2"}],"container-title":["Statistical Methods and Applications"],"original-title":[],"language":"en","link":[{"URL":"http:\/\/link.springer.com\/content\/pdf\/10.1007\/s10260-009-0116-1.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"text-mining"},{"URL":"http:\/\/link.springer.com\/article\/10.1007\/s10260-009-0116-1\/fulltext.html","content-type":"text\/html","content-version":"vor","intended-application":"text-mining"},{"URL":"http:\/\/link.springer.com\/content\/pdf\/10.1007\/s10260-009-0116-1","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2019,5,29]],"date-time":"2019-05-29T11:46:34Z","timestamp":1559130394000},"score":1,"resource":{"primary":{"URL":"http:\/\/link.springer.com\/10.1007\/s10260-009-0116-1"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2009,3,24]]},"references-count":33,"journal-issue":{"issue":"1","published-print":{"date-parts":[[2010,3]]}},"alternative-id":["116"],"URL":"https:\/\/doi.org\/10.1007\/s10260-009-0116-1","relation":{},"ISSN":["1618-2510","1613-981X"],"issn-type":[{"value":"1618-2510","type":"print"},{"value":"1613-981X","type":"electronic"}],"subject":[],"published":{"date-parts":[[2009,3,24]]}}}