{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2024,9,4]],"date-time":"2024-09-04T23:41:38Z","timestamp":1725493298293},"publisher-location":"London","reference-count":31,"publisher":"Springer London","isbn-type":[{"type":"print","value":"9781846282232"},{"type":"electronic","value":"9781846282249"}],"license":[{"start":{"date-parts":[[2006,1,1]],"date-time":"2006-01-01T00:00:00Z","timestamp":1136073600000},"content-version":"tdm","delay-in-days":0,"URL":"http:\/\/www.springer.com\/tdm"}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":[],"published-print":{"date-parts":[[2006]]},"DOI":"10.1007\/1-84628-224-1_10","type":"book-chapter","created":{"date-parts":[[2007,10,26]],"date-time":"2007-10-26T03:50:33Z","timestamp":1193370633000},"page":"122-133","source":"Crossref","is-referenced-by-count":2,"title":["Applying Bayesian Networks for Meteorological Data Mining"],"prefix":"10.1007","author":[{"suffix":"Jr","given":"Estevam R.","family":"Hruschka","sequence":"first","affiliation":[]},{"given":"Eduardo R.","family":"Hruschka","sequence":"additional","affiliation":[]},{"given":"Nelson F. F.","family":"Ebecken","sequence":"additional","affiliation":[]}],"member":"297","reference":[{"key":"10_CR1","first-page":"239","volume":"5","author":"J. Basak","year":"2004","unstructured":"Basak, J., Sudarshan, A., Trivedi, D., Santhanam, M.S., Weather Data Mining Using Independent Component Analysis, Journal of Machine Learning Research, n.5, pp. 239\u2013253, 2004.","journal-title":"Journal of Machine Learning Research"},{"doi-asserted-by":"crossref","unstructured":"Cano, R., Sordo, C., Guti\u00e9rrez, J.M., Applications of Bayesian Networks in Meteorology, Advances in Bayesian Networks, G\u00e1mez, J.A. et al. eds., pp. 309\u2013327, Springer, 2004.","key":"10_CR2","DOI":"10.1007\/978-3-540-39879-0_17"},{"doi-asserted-by":"crossref","unstructured":"Cofi\u00f1o, A.S., Guti\u00e9rrez, J.M., Jakubiak, B., Melonek, M., Implementation of data mining techniques for meteorological applications. In: Realizing Teracomputing, Zwieflhofer, W. & N. Kreitz eds., pp. 256\u2013271, World Scientific Publishing, 2003.","key":"10_CR3","DOI":"10.1142\/9789812704832_0012"},{"key":"10_CR4","doi-asserted-by":"publisher","first-page":"79","DOI":"10.1023\/A:1009730122752","volume":"1","author":"D. Heckerman","year":"1997","unstructured":"Heckerman, D. \u201cBayesian networks for data mining,\u201d Data Mining and Knowledge Discovery, vol. 1, pp. 79\u2013119, 1997.","journal-title":"Data Mining and Knowledge Discovery"},{"key":"10_CR5","first-page":"453","volume":"87","author":"E. R. Hruschka","year":"2002","unstructured":"Hruschka JR., E. R., Hruschka, E. R., Ebecken, N. F. F. A Data Preparation Bayesian Approach for a Clustering Genetic Algorithm. In: Frontiers in Artificial Intelligence and Applications, Soft Computing Systems: Design, Management and Applications, IOS Press, v.87, pp. 453\u2013461, 2002.","journal-title":"Frontiers in Artificial Intelligence and Applications, Soft Computing Systems: Design, Management and Applications"},{"doi-asserted-by":"crossref","unstructured":"Blum, A.L., Langley, P., Selection of Relevant Features and Examples in Machine Learning, Artificial Intelligence, pp. 245\u2013271, 1997.","key":"10_CR6","DOI":"10.1016\/S0004-3702(97)00063-5"},{"key":"10_CR7","series-title":"Lecture Notes in Artificial Intelligence","first-page":"370","volume-title":"Feature Selection by Bayesian Networks In: The Seventeenth Canadian Conference on Artificial Intelligence","author":"E. R. Hruschka","year":"2004","unstructured":"Hruschka JR., E. R., Hruschka, E. R., Ebecken, N. F. F. Feature Selection by Bayesian Networks In: The Seventeenth Canadian Conference on Artificial Intelligence, 2004, London, Ontario. Lecture Notes in Artificial Intelligence. Berlin: Springer-Verlag, v. 3060, pp. 370\u2013379, 2004."},{"volume-title":"Probabilistic Reasoning in Intelligent Systems: Networks of Plausible Inference","year":"1988","author":"J. Pearl","unstructured":"Pearl, J., Probabilistic Reasoning in Intelligent Systems: Networks of Plausible Inference, Morgan Kaufmann, San Mateo, CA, 1988.","key":"10_CR8"},{"issue":"1\u20132","key":"10_CR9","doi-asserted-by":"publisher","first-page":"95","DOI":"10.1023\/A:1020249912095","volume":"50","author":"N. Friedman","year":"2003","unstructured":"Friedman, N. and Koller, D., Being Bayesian about network structure. A Bayesian approach to structure discovery in Bayesian networks, Machine Leraning 50(1\u20132): 95\u2013125, 2003.","journal-title":"Machine Leraning"},{"unstructured":"Cooper, Gregory F. NESTOR: A computer-based medical diagnostic aid that integrates causal and probabilistic knowledge, PhD. thesis, Rep. No. STAN-CS-84-48 (also HPP-84-48) Dept. of Computer Science, Stanford Univ., CA, 1984.","key":"10_CR10"},{"key":"10_CR11","doi-asserted-by":"publisher","first-page":"507","DOI":"10.1162\/153244303321897717","volume":"3","author":"D. M. Chickering","year":"2002","unstructured":"Chickering, D. M., Optimal Structure Identification with Greedy Search, Journal of Machine Learning Research, (3):507\u2013554, 2002.","journal-title":"Journal of Machine Learning Research"},{"doi-asserted-by":"crossref","unstructured":"Spirtes, P., Glymour, C. and Scheines, R., Causation, Prediction, and Search, (Adaptive Computation and Machine Learning), 2nd edition, Bradford Books, 2001.","key":"10_CR12","DOI":"10.7551\/mitpress\/1754.001.0001"},{"issue":"1\u20132","key":"10_CR13","doi-asserted-by":"publisher","first-page":"43","DOI":"10.1016\/S0004-3702(02)00191-1","volume":"137","author":"J. Cheng","year":"2002","unstructured":"Cheng, J., Greiner, R., Kelly, J., Bell, D., Liu, W.R., Learning Bayesian networks from data: An information-theory based approach. Artificial Intelligence, 137(1\u20132): 43\u201390, 2002.","journal-title":"Artificial Intelligence"},{"key":"10_CR14","first-page":"309","volume":"9","author":"G. Cooper","year":"1992","unstructured":"Cooper G. & Herskovitz, E.. A Bayesian Method for the Induction of Probabilistic Networks from Data. Machine Learning, 9, 309\u2013347, 1992.","journal-title":"Machine Learning"},{"volume-title":"Induction of Selective Bayesian Classifiers","year":"1994","author":"P. Langley","unstructured":"Langley, P. & Sage, S., Induction of Selective Bayesian Classifiers. Proceedings of the Tenth Conference on Uncertainty in Artificial Intelligence, Seattle, 1994.","key":"10_CR15"},{"key":"10_CR16","first-page":"275","volume":"9","author":"J. R. Anderson","year":"1992","unstructured":"Anderson, J. R. & Matessa, M., Explorations of an Incremental Bayesian Algorithm for categorization. Machine Learning, 9, 275\u2013308, 1992.","journal-title":"Machine Learning"},{"key":"10_CR17","doi-asserted-by":"publisher","first-page":"103","DOI":"10.1016\/j.ins.2003.03.019","volume":"163","author":"W. H. Hsu","year":"2004","unstructured":"Hsu, W. H., Genetic Wrappers for feature selection in decision tree induction and variable ordering in Bayesian network structure learning, Information Science, 163, pp. 103\u2013122,2004.","journal-title":"Information Science"},{"unstructured":"Cheng, J. and Greiner, R., Comparing Bayesian Network Classifiers, Proc. of the Fifteenth Conference on Uncertainty in Artificial Intelligence (UAI\u2019 99), Sweden, pp. 101\u2013108, 1999.","key":"10_CR18"},{"key":"10_CR19","series-title":"Lecture Notes AI","first-page":"440","volume-title":"Proceedings of the 16th Australian Conference on AI (AI 03)","author":"Y. Ying","year":"2003","unstructured":"Ying, Y. and Webb, G., On Why Discretization Works for Naive-Bayes Classifiers. In Proceedings of the 16th Australian Conference on AI (AI 03), Lecture Notes AI 2903, 440\u2013452. Berlin: Springer, 2003."},{"unstructured":"Ying, Y., Discretization for Naive-Bayes Learning. PhD. Thesis, Monash University, 2003b. http:\/\/www.cs.uvm.edu\/~yyang\/Yingthesis.pdf","key":"10_CR20"},{"volume-title":"Data Mining \u2014 Practical Machine Learning Tools and Techniques with Java Implementations","year":"2000","author":"I. H. Witten","unstructured":"Witten, I. H., Frank, E., Data Mining \u2014 Practical Machine Learning Tools and Techniques with Java Implementations, Morgan Kaufmann Publishers, USA, 2000.","key":"10_CR21"},{"key":"10_CR22","first-page":"1","volume":"39","author":"A. P. Dempster","year":"1977","unstructured":"Dempster, A. P., Laird, N. M., Rubin, D. B., Maximum Likelihood from Incomplete Data via the EM algorithm, Journal of the Royal Statistical Society B, 39,1\u201339, 1977.","journal-title":"Journal of the Royal Statistical Society B"},{"key":"10_CR23","doi-asserted-by":"publisher","first-page":"398","DOI":"10.2307\/2289776","volume":"85","author":"A.E. Gelfand","year":"1990","unstructured":"Gelfand, A.,E. and Smith, A. F. M., Sampling-based approaches to calculating marginal densities. J. American Statistical Association, 85:398\u2013409, 1990.","journal-title":"J. American Statistical Association"},{"key":"10_CR24","doi-asserted-by":"publisher","first-page":"167","DOI":"10.2307\/2685208","volume":"46","author":"G. Casella","year":"1992","unstructured":"Casella, G. and George, E. I., \u201cExplaining the Gibbs sampler,\u201d Amer. Statist., vol. 46, pp. 167\u2013174, 1992.","journal-title":"Amer. Statist."},{"unstructured":"Bigus, J. P., Data Mining with Neural Networks, First edition, USA, McGraw-Hill, 1996.","key":"10_CR25"},{"unstructured":"Han, J. and Kamber, M., Data Mining, Concepts and Techniques. Morgan Kaufmann, 2001.","key":"10_CR26"},{"key":"10_CR27","doi-asserted-by":"publisher","first-page":"1371","DOI":"10.1162\/153244303322753715","volume":"3","author":"J. Reunanen","year":"2003","unstructured":"Reunanen, J., Overfitting in Making Comparissons Between Variable Selection Methods, Journal of Machine Learning Research 3, pp. 1371\u20131382, 2003.","journal-title":"Journal of Machine Learning Research"},{"doi-asserted-by":"crossref","unstructured":"Liu, H. and Motoda, H., Feature Selection for Knowledge Discovery and Data Mining. Kluwer Academic, 1998.","key":"10_CR28","DOI":"10.1007\/978-1-4615-5689-3"},{"key":"10_CR29","doi-asserted-by":"publisher","first-page":"1157","DOI":"10.1162\/153244303322753616","volume":"3","author":"I. Guyon","year":"2003","unstructured":"Guyon, I., Elisseeff, A., An Introduction to Variable and Feature Selection, Journal of Machine Learning Research 3, pp. 1157\u20131182, 2003.","journal-title":"Journal of Machine Learning Research"},{"volume-title":"Statistical Analysis with Missing Data","year":"1987","author":"R. Little","unstructured":"Little, R., & Rubin, D. B., Statistical Analysis with Missing Data. Wiley, New York, 1987.","key":"10_CR30"},{"key":"10_CR31","first-page":"157","volume":"50","author":"S. L. Lauritzen","year":"1988","unstructured":"Lauritzen, S. L., & Spiegelhalter, D. J., Local computations with probabilities on graphical structures and their application to expert systems. J. Royal Statistical Society B, 50, 157\u2013224, 1988.","journal-title":"J. Royal Statistical Society B"}],"container-title":["Applications and Innovations in Intelligent Systems XIII"],"original-title":[],"language":"en","link":[{"URL":"http:\/\/link.springer.com\/content\/pdf\/10.1007\/1-84628-224-1_10","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2020,1,29]],"date-time":"2020-01-29T08:23:07Z","timestamp":1580286187000},"score":1,"resource":{"primary":{"URL":"http:\/\/link.springer.com\/10.1007\/1-84628-224-1_10"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2006]]},"ISBN":["9781846282232","9781846282249"],"references-count":31,"URL":"http:\/\/dx.doi.org\/10.1007\/1-84628-224-1_10","relation":{},"subject":[],"published":{"date-parts":[[2006]]}}}