{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,3,27]],"date-time":"2025-03-27T17:14:13Z","timestamp":1743095653834,"version":"3.40.3"},"publisher-location":"Cham","reference-count":17,"publisher":"Springer International Publishing","isbn-type":[{"type":"print","value":"9783030200541"},{"type":"electronic","value":"9783030200558"}],"license":[{"start":{"date-parts":[[2019,5,1]],"date-time":"2019-05-01T00:00:00Z","timestamp":1556668800000},"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\/978-3-030-20055-8_24","type":"book-chapter","created":{"date-parts":[[2019,4,30]],"date-time":"2019-04-30T09:16:38Z","timestamp":1556615798000},"page":"251-260","update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":7,"title":["Addressing Low Dimensionality Feature Subset Selection: ReliefF(-k) or Extended Correlation-Based Feature Selection(eCFS)?"],"prefix":"10.1007","author":[{"given":"Antonio J.","family":"Tall\u00f3n-Ballesteros","sequence":"first","affiliation":[]},{"given":"Lu\u00eds","family":"Cavique","sequence":"additional","affiliation":[]},{"given":"Simon","family":"Fong","sequence":"additional","affiliation":[]}],"member":"297","published-online":{"date-parts":[[2019,5,1]]},"reference":[{"issue":"1","key":"24_CR1","first-page":"37","volume":"6","author":"DW Aha","year":"1991","unstructured":"Aha, D.W., Kibler, D., Albert, M.K.: Instance-based learning algorithms. Mach. Learn. 6(1), 37\u201366 (1991)","journal-title":"Mach. Learn."},{"key":"24_CR2","doi-asserted-by":"publisher","first-page":"101","DOI":"10.1016\/j.csi.2017.05.004","volume":"57","author":"B Bilalli","year":"2018","unstructured":"Bilalli, B., Abell\u00f3, A., Aluja-Banet, T., Wrembel, R.: Intelligent assistance for data pre-processing. Comput. Stand. Interfaces 57, 101\u2013109 (2018)","journal-title":"Comput. Stand. Interfaces"},{"key":"24_CR3","doi-asserted-by":"crossref","unstructured":"Chen, Y., Li, Y., Cheng, X.-Q., Guo, L.: Survey and taxonomy of feature selection algorithms in intrusion detection system. In: International Conference on Information Security and Cryptology, pp. 153\u2013167. Springer, Heidelberg (2006)","DOI":"10.1007\/11937807_13"},{"key":"24_CR4","doi-asserted-by":"publisher","first-page":"551","DOI":"10.1007\/978-3-319-59773-7_56","volume-title":"Biomedical Applications Based on Natural and Artificial Computing","author":"Sung-Bae Cho","year":"2017","unstructured":"Cho, S.-B., Tall\u00f3n-Ballesteros, A.J.: Visual tools to lecture data analytics and engineering. In: International Work-Conference on the Interplay Between Natural and Artificial Computation, pp. 551\u2013558. Springer, Heidelberg (2017)"},{"issue":"1","key":"24_CR5","doi-asserted-by":"publisher","first-page":"21","DOI":"10.1109\/TIT.1967.1053964","volume":"13","author":"T Cover","year":"1967","unstructured":"Cover, T., Hart, P.: Nearest neighbor pattern classification. Inf. Theor. IEEE Transact. 13(1), 21\u201327 (1967)","journal-title":"Inf. Theor. IEEE Transact."},{"key":"24_CR6","unstructured":"Frank, E., Witten, I.H.: Generating accurate rule sets without global optimization. In: Shavlik, J. (eds.) Fifteenth International Conference on Machine Learning, pp. 144\u2013151. Morgan Kaufmann (1998)"},{"issue":"1","key":"24_CR7","doi-asserted-by":"publisher","first-page":"10","DOI":"10.1145\/1656274.1656278","volume":"11","author":"M Hall","year":"2009","unstructured":"Hall, M., Frank, E., Holmes, G., Pfahringer, B., Reutemann, P., Witten, I.H.: The weka data mining software: an update. ACM SIGKDD Explor. Newsl. 11(1), 10\u201318 (2009)","journal-title":"ACM SIGKDD Explor. Newsl."},{"key":"24_CR8","unstructured":"Hall, M.A.: Correlation-based feature selection for machine learning. Ph.D thesis, University of Waikato, Hamilton, New Zealand (1999)"},{"key":"24_CR9","doi-asserted-by":"publisher","first-page":"919","DOI":"10.1016\/j.procs.2016.07.111","volume":"91","author":"J Miao","year":"2016","unstructured":"Miao, J., Niu, L.: A survey on feature selection. Proc. Comput. Sci. 91, 919\u2013926 (2016)","journal-title":"Proc. Comput. Sci."},{"key":"24_CR10","volume-title":"C4.5: Programs for Machine Learning","author":"JR Quinlan","year":"1993","unstructured":"Quinlan, J.R.: C4.5: Programs for Machine Learning, vol. 1. Morgan kaufmann, Burlington (1993)"},{"key":"24_CR11","doi-asserted-by":"crossref","unstructured":"Shapiro, A., Niblett, T.: Automatic induction of classification rules for a chess endgame. In: Advances in Computer Chess, pp. 73\u201392. Elsevier (1982)","DOI":"10.1016\/B978-0-08-026898-9.50010-3"},{"key":"24_CR12","doi-asserted-by":"crossref","unstructured":"Tall\u00f3n-Ballesteros, A.J., Correia, L., Xue, B.: Featuring the attributes in supervised machine learning. In: International Conference on Hybrid Artificial Intelligence Systems, pp. 350\u2013362. Springer (2018)","DOI":"10.1007\/978-3-319-92639-1_29"},{"key":"24_CR13","doi-asserted-by":"crossref","unstructured":"Tall\u00f3n-Ballesteros, A.J., Riquelme, J.C.: Low dimensionality or same subsets as a result of feature selection: an in-depth roadmap. In: International Work-Conference on the Interplay Between Natural and Artificial Computation, pp. 531\u2013539. Springer (2017)","DOI":"10.1007\/978-3-319-59773-7_54"},{"issue":"3","key":"24_CR14","doi-asserted-by":"publisher","first-page":"242","DOI":"10.1080\/09540091.2016.1149146","volume":"28","author":"AJ Tall\u00f3n-Ballesteros","year":"2016","unstructured":"Tall\u00f3n-Ballesteros, A.J., Riquelme, J.C., Ruiz, R.: Merging subsets of attributes to improve a hybrid consistency-based filter: a case of study in product unit neural networks. Connect. Sci. 28(3), 242\u2013257 (2016)","journal-title":"Connect. Sci."},{"key":"24_CR15","volume-title":"Introduction to Data Mining","author":"P-N Tan","year":"2018","unstructured":"Tan, P.-N.: Introduction to Data Mining. Pearson Education, India (2018)"},{"key":"24_CR16","doi-asserted-by":"publisher","DOI":"10.1007\/978-1-4757-2440-0","volume-title":"The Nature of Statistical Learning Theory","author":"VN Vapnik","year":"1995","unstructured":"Vapnik, V.N.: The Nature of Statistical Learning Theory. Springer, Heidelberg (1995)"},{"key":"24_CR17","unstructured":"Wirth, R., Hipp, J.: CRISP-DM: towards a standard process model for data mining. In: Proceedings of the 4th International Conference on the Practical Applications of Knowledge Discovery and Data Mining, pp. 29\u201339. Citeseer (2000)"}],"container-title":["Advances in Intelligent Systems and Computing","14th International Conference on Soft Computing Models in Industrial and Environmental Applications (SOCO 2019)"],"original-title":[],"language":"en","link":[{"URL":"http:\/\/link.springer.com\/content\/pdf\/10.1007\/978-3-030-20055-8_24","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2019,5,18]],"date-time":"2019-05-18T04:12:22Z","timestamp":1558152742000},"score":1,"resource":{"primary":{"URL":"http:\/\/link.springer.com\/10.1007\/978-3-030-20055-8_24"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2019,5,1]]},"ISBN":["9783030200541","9783030200558"],"references-count":17,"URL":"https:\/\/doi.org\/10.1007\/978-3-030-20055-8_24","relation":{},"ISSN":["2194-5357","2194-5365"],"issn-type":[{"type":"print","value":"2194-5357"},{"type":"electronic","value":"2194-5365"}],"subject":[],"published":{"date-parts":[[2019,5,1]]},"assertion":[{"value":"1 May 2019","order":1,"name":"first_online","label":"First Online","group":{"name":"ChapterHistory","label":"Chapter History"}},{"value":"SOCO","order":1,"name":"conference_acronym","label":"Conference Acronym","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"International Workshop on Soft Computing Models in Industrial and Environmental Applications","order":2,"name":"conference_name","label":"Conference Name","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"Seville","order":3,"name":"conference_city","label":"Conference City","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"Spain","order":4,"name":"conference_country","label":"Conference Country","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"2019","order":5,"name":"conference_year","label":"Conference Year","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"13 May 2019","order":7,"name":"conference_start_date","label":"Conference Start Date","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"15 May 2019","order":8,"name":"conference_end_date","label":"Conference End Date","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"14","order":9,"name":"conference_number","label":"Conference Number","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"socomoin2019","order":10,"name":"conference_id","label":"Conference ID","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"http:\/\/2019.sococonference.eu\/","order":11,"name":"conference_url","label":"Conference URL","group":{"name":"ConferenceInfo","label":"Conference Information"}}]}}