{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2024,9,4]],"date-time":"2024-09-04T17:37:24Z","timestamp":1725471444428},"reference-count":29,"publisher":"Springer US","isbn-type":[{"type":"print","value":"9780387346557"}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":[],"DOI":"10.1007\/978-0-387-34749-3_3","type":"book-chapter","created":{"date-parts":[[2006,10,10]],"date-time":"2006-10-10T19:54:54Z","timestamp":1160510094000},"page":"21-30","source":"Crossref","is-referenced-by-count":4,"title":["Improving the k-NN method: Rough Set in edit training set"],"prefix":"10.1007","author":[{"given":"Yail\u00e9","family":"Caballero","sequence":"first","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Rafael","family":"Bello","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Delia","family":"Alvarez","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Maria M.","family":"Gareia","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Yaimara","family":"Pizano","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"297","reference":[{"key":"3_CR1","unstructured":"Aha, D.W. Case-based Learning Algorithms. Proceedings of the DARPA Case-based Reasoning Workshop. Morgan Kaufmann Publishers. 1991."},{"key":"3_CR2","unstructured":"Domingos, P. Unifying instance-based and rule-based induction. International Joint Conference on Artificial Intelligence. 1995."},{"key":"3_CR3","unstructured":"Lopez, R.M. and Armengol, E.. Machine learning from examples: Inductive and Lazy methods."},{"key":"3_CR4","first-page":"103","volume-title":"Proceedings 9th Symposium on Pattern Recognition and Image Analysis","author":"R. Barandela","year":"2001","unstructured":"Barandela, R. et al.. The nearest neighbor rule and the reduction of the training sample size. Proceedings 9th Symposium on Pattern Recognition and Image Analysis, 1, 103\u2013108, Castellon, Espa\u00f1a, 2001"},{"key":"3_CR5","doi-asserted-by":"publisher","first-page":"341","DOI":"10.1007\/BF01001956","volume":"11","author":"Z. Pawlak","year":"1982","unstructured":"Pawlak, Z.. Rough sets. International Journal of Information & Computer Sciences 11, 341\u2013356, 1982.","journal-title":"International Journal of Information & Computer Sciences"},{"key":"3_CR6","unstructured":"Komorowski, J. Pawlak, Z. et al.. Rough Sets: A tutorial. In Pal, S.K. and Skowron, A. (Eds) Rough Fuzzy Hybridization: A new trend in decision-making. Springer, pp. 3\u201398. 1999."},{"key":"3_CR7","doi-asserted-by":"crossref","unstructured":"Polkowski, L.. Rough sets: Mathematical foundations. Physica-Verlag, p. 574. Berlin, Germany. 2002.","DOI":"10.1007\/978-3-7908-1776-8"},{"key":"3_CR8","doi-asserted-by":"publisher","first-page":"641","DOI":"10.1016\/S0377-2217(01)00259-4","volume":"141","author":"F.E. Tay","year":"2002","unstructured":"Tay, F.E. and Shen, L.. Economic and financial prediction using rough set model. European Journal of Operational Research 141, pp. 641\u2013659. 2002.","journal-title":"European Journal of Operational Research"},{"key":"3_CR9","doi-asserted-by":"publisher","first-page":"1","DOI":"10.1016\/S0377-2217(00)00167-3","volume":"129","author":"S. Greco","year":"2001","unstructured":"Greco, S. Et al. Rough sets theory for multicriteria decision analysis. European Journal of Operational Research 129, pp. 1\u201347, 2001.","journal-title":"European Journal of Operational Research"},{"key":"3_CR10","unstructured":"Pal, S.K. and Skowron, A. (Eds). Rough Fuzzy Hybridization: a new trend in decision-making. Springer-Verlag, 1999."},{"key":"3_CR11","unstructured":"Kohavi, R. and Frasca, B. Useful feature subsets and Rough set Reducts. Proceedings of the Third International Workshop on Rough Sets and Soft Computing. 1994."},{"key":"3_CR12","unstructured":"Maudal, O. Preprocessing data for neural network based classifiers: Rough sets vs Principal Component Analysis. Project report, Dept. of Artificial Intelligence, University of Edinburgh. 1996."},{"key":"3_CR13","doi-asserted-by":"crossref","unstructured":"Koczkodaj, W.W. et al.. Myths about Rough Set Theory. Comm. of the ACM, vol. 41, no. 11, nov. 1998.","DOI":"10.1145\/287831.287847"},{"key":"3_CR14","doi-asserted-by":"publisher","first-page":"199","DOI":"10.1023\/A:1011219601502","volume":"16","author":"N. Zhong","year":"2001","unstructured":"Zhong, N. et al.. Using Rough sets with heuristics for feature selection. Journal of Intelligent Information Systems, 16, 199\u2013214. 2001.","journal-title":"Journal of Intelligent Information Systems"},{"key":"3_CR15","doi-asserted-by":"crossref","unstructured":"Pal, S.K. et al. Web mining in Soft Computing framework: Relevance, State of the art and Future Directions. IEEE Transactions on Neural Networks, 2002.","DOI":"10.1109\/TNN.2002.1031947"},{"key":"3_CR16","doi-asserted-by":"publisher","first-page":"431","DOI":"10.1109\/TIT.1972.1054809","volume":"IT-18-3","author":"G. W. Gates","year":"1972","unstructured":"Gates, G. W. The Reduced Nearest Neighbor Rule. IEEE Transactions on Information Theory, IT-18-3, pp. 431\u2013433. 1972.","journal-title":"IEEE Transactions on Information Theory"},{"key":"3_CR17","doi-asserted-by":"crossref","unstructured":"Ritter, G. L. Woodruff, H. B. Lowry, S. R. Isenhour, T. L. An Algorithm for a Selective Nearest Neighbor Decision Rule. IEEE Transactions on Information Theory, 21\u20136, November, pp. 665\u2013669. 1975.","DOI":"10.1109\/TIT.1975.1055464"},{"key":"3_CR18","doi-asserted-by":"crossref","first-page":"72","DOI":"10.1162\/neco.1995.7.1.72","volume":"7-1","author":"D. G. Lowe","year":"1995","unstructured":"Lowe, David G. Similarity Metric Learning for a Variable-Kernel Classifier. Neural Computation., 7-1, pp. 72\u201385. 1995.","journal-title":"Neural Computation"},{"key":"3_CR19","volume-title":"Reduction Techniques for Exemplar-Based Learning Algorithms. Machine Learning","author":"Randall. Wilson","year":"1998","unstructured":"Wilson, Randall. Martinez, Tony R. Reduction Techniques for Exemplar-Based Learning Algorithms. Machine Learning. Computer Science Department, Brigham Young University. USA 1998."},{"key":"3_CR20","doi-asserted-by":"crossref","unstructured":"Barandela, Ricardo; Gasca, Eduardo, Alejo, Roberto. Correcting the Training Data. Published in \u201cPattern Recognition and String Matching\u201d, D. Chen and X. Cheng (eds.), Kluwer, 2002.","DOI":"10.1007\/978-1-4613-0231-5_1"},{"key":"3_CR21","unstructured":"Devijver, P. and Kittler, J. Pattern Recognition: A Statistical Approach, Prentice Hall, 1982."},{"key":"3_CR22","doi-asserted-by":"publisher","first-page":"53","DOI":"10.1023\/A:1014043630878","volume":"6","author":"H. Brighton","year":"2002","unstructured":"Brighton, H. and Mellish, C. Advances in Instance Selection for Instance-Based Learning Algorithms. Data Mining and Knowledge Discovery, 6, pp. 53\u2013172, 2002.","journal-title":"Data Mining and Knowledge Discovery"},{"key":"3_CR23","doi-asserted-by":"publisher","first-page":"1015","DOI":"10.1016\/S0167-8655(02)00225-8","volume":"24\u20137","author":"J. S. S\u00e1nchez","year":"2003","unstructured":"S\u00e1nchez, J. S., Barandela, R., Marqu\u00e9s, A. I., Alejo, R., Badenas, J. Analysis of new techniques to obtain quality training sets. Pattern Recognition Letters, 24\u20137, pp. 1015\u20131022, 2003.","journal-title":"Pattern Recognition Letters"},{"key":"3_CR24","doi-asserted-by":"crossref","unstructured":"Jiang Y., Zhou, Z.-H. Editing training data for kNN classifiers with neural network ensemble. In: Advances in Neural Networks, LNCS 3173, pp. 356\u2013361, Springer-Verlag, 2004.","DOI":"10.1007\/978-3-540-28647-9_60"},{"key":"3_CR25","first-page":"280","volume":"3578","author":"J. A. Olvera-L\u00f3pez","year":"2005","unstructured":"Olvera-L\u00f3pez, Jos\u00e9 A., Carrasco-Ochoa, J. Ariel and Mart\u00ednez-Trinidad, Jos\u00e9 Fco. Sequential Search for Decremental Edition. Proceedings of the 6th International Conference on Intelligent Data Engineering and Automated Learning, IDEAL 2005. Brisbane, Australia, vol 3578, pp. 280\u2013285, LNCS Springer-Verlag, 2005.","journal-title":"Sequential Search for Decremental Edition"},{"key":"3_CR26","unstructured":"Garc\u00eda, M. and Shulcloper, J. Selecting Prototypes in Mixed Incomplete Data. Lectures Notes in computer Science (LNCS 3773), pp. 450\u2013460. Springer, Verlag, Berlin Heidelberg. New York. ISSN 0302-9743 ISBN 978-3-540-29850."},{"key":"3_CR27","volume-title":"Techniques of approximation II: Non parametric approximation","author":"J.B. Cortijo","year":"2001","unstructured":"Cortijo, J.B. Techniques of approximation II: Non parametric approximation. Thesis. Department of Computer Science and Artificial Intelligence, Universidad de Granada, Spain. October 2001."},{"issue":"5","key":"3_CR28","first-page":"403","volume":"49","author":"D. Bell","year":"1998","unstructured":"Bell, D. and Guan, J. Computational methods for rough classification and discovery. Journal of ASIS 49,5, pp. 403\u2013414. 1998.","journal-title":"Journal of ASIS"},{"key":"3_CR29","unstructured":"Deogun, J.S. et al. Exploiting upper approximations in the rough set methodology. In Proceedings of First International Conference on Knowledge Discovery and Data Mining, Fayyad, U. Y Uthurusamy, (Eds.), Canada, pp. 69\u201374. 1995."}],"container-title":["IFIP International Federation for Information Processing","Professional Practice in Artificial Intelligence"],"original-title":[],"language":"en","link":[{"URL":"http:\/\/link.springer.com\/content\/pdf\/10.1007\/978-0-387-34749-3_3.pdf","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2020,11,17]],"date-time":"2020-11-17T16:45:05Z","timestamp":1605631505000},"score":1,"resource":{"primary":{"URL":"http:\/\/link.springer.com\/10.1007\/978-0-387-34749-3_3"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[null]]},"ISBN":["9780387346557"],"references-count":29,"URL":"https:\/\/doi.org\/10.1007\/978-0-387-34749-3_3","relation":{},"subject":[]}}