{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2024,9,10]],"date-time":"2024-09-10T17:09:08Z","timestamp":1725988148658},"publisher-location":"Cham","reference-count":38,"publisher":"Springer International Publishing","isbn-type":[{"type":"print","value":"9783319987019"},{"type":"electronic","value":"9783319987026"}],"license":[{"start":{"date-parts":[[2018,8,17]],"date-time":"2018-08-17T00:00:00Z","timestamp":1534464000000},"content-version":"unspecified","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":[[2019]]},"DOI":"10.1007\/978-3-319-98702-6_24","type":"book-chapter","created":{"date-parts":[[2018,8,16]],"date-time":"2018-08-16T05:27:55Z","timestamp":1534397275000},"page":"200-207","update-policy":"http:\/\/dx.doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":1,"title":["A Genetic Programming Approach Applied to Feature Selection from Medical Data"],"prefix":"10.1007","author":[{"given":"Jos\u00e9 A.","family":"Castellanos-Garz\u00f3n","sequence":"first","affiliation":[]},{"given":"Juan","family":"Ramos","sequence":"additional","affiliation":[]},{"given":"Yeray Mezquita","family":"Mart\u00edn","sequence":"additional","affiliation":[]},{"given":"Juan F.","family":"de Paz","sequence":"additional","affiliation":[]},{"given":"Ernesto","family":"Costa","sequence":"additional","affiliation":[]}],"member":"297","published-online":{"date-parts":[[2018,8,17]]},"reference":[{"key":"24_CR1","series-title":"Natural Computing Series","doi-asserted-by":"publisher","DOI":"10.1007\/3-540-49607-6","volume-title":"Classification and Learning Using Genetic Algorithms: Applications in Bioinformatics and Web Intelligence","author":"S Bandyopadhyay","year":"2007","unstructured":"Bandyopadhyay, S., Pal, S.K.: Classification and Learning Using Genetic Algorithms: Applications in Bioinformatics and Web Intelligence. Natural Computing Series. Springer, Heidelberg (2007). \nhttps:\/\/doi.org\/10.1007\/3-540-49607-6"},{"key":"24_CR2","unstructured":"Bonelli, P., Parodi, A.: An efficient classifier system and its experimental comparison with two representative learning methods on three medical domains. In: Proceedings of the 4th International Conference on Genetic Algorithms (ICGA), pp. 288\u2013295 (1991)"},{"key":"24_CR3","doi-asserted-by":"publisher","first-page":"43","DOI":"10.1016\/j.artmed.2005.06.002","volume":"36","author":"JH Hong","year":"2006","unstructured":"Hong, J.H., Cho, S.B.: The classification of cancer based on DNA microarray data that uses diverse ensemble genetic programming. Artif. Intell. Med. 36, 43\u201358 (2006)","journal-title":"Artif. Intell. Med."},{"key":"24_CR4","doi-asserted-by":"publisher","first-page":"353","DOI":"10.1109\/TCBB.2007.70245","volume":"6","author":"TP Kumar","year":"2009","unstructured":"Kumar, T.P., Iba, H.: Prediction of cancer class with majority voting genetic programming classifier using gene expression data. IEEE\/ACM Trans. Comput. Biol. Bioinf. 6, 353\u2013367 (2009)","journal-title":"IEEE\/ACM Trans. Comput. Biol. Bioinf."},{"key":"24_CR5","first-page":"183","volume":"2","author":"R Kumar","year":"2012","unstructured":"Kumar, R., Verma, R.: Classification rule discovery for diabetes patients by using genetic programming. Int. J. Soft Comput. Eng. (IJSCE) 2, 183\u2013185 (2012)","journal-title":"Int. J. Soft Comput. Eng. (IJSCE)"},{"key":"24_CR6","doi-asserted-by":"publisher","first-page":"86","DOI":"10.1093\/bib\/bbk007","volume":"7","author":"P Larraaga","year":"2006","unstructured":"Larraaga, P., et al.: Machine learning in bioinformatics. Briefings Bioinf. 7, 86\u2013112 (2006)","journal-title":"Briefings Bioinf."},{"key":"24_CR7","doi-asserted-by":"publisher","first-page":"331","DOI":"10.1093\/bioinformatics\/btn644","volume":"25","author":"KH Liu","year":"2009","unstructured":"Liu, K.H., Xu, C.G.: A genetic programming-based approach to the classification of multiclass microarray datasets. Bioinformatics 25, 331\u2013337 (2009)","journal-title":"Bioinformatics"},{"key":"24_CR8","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-642-16615-0","volume-title":"Multiobjective Genetic Algorithms for Clustering: Applications in Data Mining and Bioinformatics","author":"U Maulik","year":"2011","unstructured":"Maulik, U., Bandyopadhyay, S., Mukhopadhyay, A.: Multiobjective Genetic Algorithms for Clustering: Applications in Data Mining and Bioinformatics. Springer, Heidelberg (2011). \nhttps:\/\/doi.org\/10.1007\/978-3-642-16615-0"},{"key":"24_CR9","doi-asserted-by":"publisher","first-page":"1","DOI":"10.1016\/S0933-3657(99)00047-0","volume":"19","author":"CA Pea-Reyes","year":"2000","unstructured":"Pea-Reyes, C.A., Sipper, M.: Evolutionary computation in medicine: an overview. Artif. Intell. Med. 19, 1\u201323 (2000)","journal-title":"Artif. Intell. Med."},{"key":"24_CR10","first-page":"539","volume":"1","author":"V Podgorelec","year":"2005","unstructured":"Podgorelec, V., Kokol, P., Stiglic, M.M., Hericko, M., Rozrnan, I.: Knowledge discovery with classification rules in a cardiovascular dataset. Comput. Methods Program. Biomed. 1, 539\u2013549 (2005)","journal-title":"Comput. Methods Program. Biomed."},{"key":"24_CR11","first-page":"2385","volume":"3","author":"J Soni","year":"2011","unstructured":"Soni, J., Ansari, U., Sharma, D., Soni, S.: Intelligent and effective heart disease prediction system using weighted associative classifiers. Int. J. Comput. Sci. Eng. (IJCSE) 3, 2385\u20132392 (2011)","journal-title":"Int. J. Comput. Sci. Eng. (IJCSE)"},{"key":"24_CR12","doi-asserted-by":"publisher","first-page":"195","DOI":"10.1016\/j.artmed.2004.02.007","volume":"32","author":"A Tsakonas","year":"2004","unstructured":"Tsakonas, A., Dounias, G., Jantzen, J., Axer, H., Bjerregaard, B., von Keyserlingk, D.G.: Evolving rule-based systems in two medical domains using genetic programming. Artif. Intell. Med. 32, 195\u2013216 (2004)","journal-title":"Artif. Intell. Med."},{"key":"24_CR13","unstructured":"Vargas, C.M.B., Chidambaram, C., Hembecker, F., Silv\u00e9rio, H.L.: A comparative study of machine learning and evolutionary computation approaches for protein secondary structure classification. In: Computational Biology and Applied Bioinformatics, pp. 239\u2013258. InTech (2011)"},{"key":"24_CR14","doi-asserted-by":"publisher","first-page":"9193","DOI":"10.1073\/pnas.87.23.9193","volume":"87","author":"WH Wolberg","year":"1990","unstructured":"Wolberg, W.H., Mangasarian, O.L.: Multisurface method of pattern separation for medical diagnosis applied to breast cytology. Proc. Natl. Acad. Sci. USA 87, 9193\u20139196 (1990)","journal-title":"Proc. Natl. Acad. Sci. USA"},{"issue":"105","key":"24_CR15","doi-asserted-by":"publisher","first-page":"295","DOI":"10.1016\/S0004-3702(98)00081-2","volume":"12","author":"P Lucas","year":"1998","unstructured":"Lucas, P.: Analysis of notions of diagnosis. Artif. Intell. 12(105), 295\u2013343 (1998)","journal-title":"Artif. Intell."},{"key":"24_CR16","doi-asserted-by":"publisher","first-page":"105","DOI":"10.1016\/S0933-3657(98)00047-5","volume":"15","author":"P Lucas","year":"1999","unstructured":"Lucas, P.: Prognostic methods in medicine. Artif. Intell. 15, 105\u2013119 (1999)","journal-title":"Artif. Intell."},{"key":"24_CR17","doi-asserted-by":"publisher","first-page":"1","DOI":"10.1007\/s12539-017-0219-6","volume":"9","author":"J Ramos","year":"2017","unstructured":"Ramos, J., Castellanos-Garz\u00f3n, J.A., Gonz\u00e1lez-Briones, A., de Paz, J.F., Corchado, J.M.: An agent-based clustering approach for gene selection in gene expression microarray. Interdiscip. Sci. Comput. Life Sci. 9, 1\u201313 (2017)","journal-title":"Interdiscip. Sci. Comput. Life Sci."},{"key":"24_CR18","series-title":"Advances in Intelligent Systems and Computing","doi-asserted-by":"publisher","first-page":"99","DOI":"10.1007\/978-3-319-40126-3_11","volume-title":"Practical Applications of Computational Biology and Bioinformatics","author":"JA Castellanos-Garz\u00f3n","year":"2016","unstructured":"Castellanos-Garz\u00f3n, J.A., Ramos, J., Gonz\u00e1lez-Briones, A., de Paz, J.F.: A clustering-based method for gene selection to classify tissue samples in lung cancer. In: Saberi Mohamad, M., Rocha, M., Fdez-Riverola, F., Dom\u00ednguez Mayo, F., De Paz, J. (eds.) PACBB 2016. AISC, vol. 477, pp. 99\u2013107. Springer, Cham (2016). \nhttps:\/\/doi.org\/10.1007\/978-3-319-40126-3_11"},{"issue":"3","key":"24_CR19","first-page":"1","volume":"4","author":"JA Castellanos-Garz\u00f3n","year":"2015","unstructured":"Castellanos-Garz\u00f3n, J.A., Ramos, J.: A gene selection approach based on clustering for classification tasks in colon cancer. ADCAIJ Adv. Distrib. Comput. Artif. Intell. J. 4(3), 1\u201310 (2015)","journal-title":"ADCAIJ Adv. Distrib. Comput. Artif. Intell. J."},{"issue":"4","key":"24_CR20","first-page":"83","volume":"4","author":"A Gonz\u00e1lez-Briones","year":"2015","unstructured":"Gonz\u00e1lez-Briones, A., Ramos, J., De Paz, J.F.: A drug identification system for intoxicated drivers based on a systematic review. ADCAIJ Adv. Distrib. Comput. Artif. Intell. J. 4(4), 83\u2013101 (2015)","journal-title":"ADCAIJ Adv. Distrib. Comput. Artif. Intell. J."},{"issue":"2","key":"24_CR21","doi-asserted-by":"publisher","first-page":"121","DOI":"10.1109\/TSMCC.2009.2033566","volume":"40","author":"PG Espejo","year":"2010","unstructured":"Espejo, P.G., Ventura, S., Herrera, F.: A survey on the application of genetic programming to classification. IEEE Trans. Syst. Man Cybern. Part C Appl. Rev. 40(2), 121\u2013144 (2010)","journal-title":"IEEE Trans. Syst. Man Cybern. Part C Appl. Rev."},{"issue":"3","key":"24_CR22","doi-asserted-by":"publisher","first-page":"283","DOI":"10.1007\/s10115-008-0171-1","volume":"19","author":"GL Pappa","year":"2009","unstructured":"Pappa, G.L., Freitas, A.A.: Evolving rule induction algorithms with multi-objective grammar-based genetic programming. Knowl. Inf. Syst. 19(3), 283\u2013309 (2009)","journal-title":"Knowl. Inf. Syst."},{"key":"24_CR23","doi-asserted-by":"publisher","first-page":"307","DOI":"10.1007\/s00500-008-0323-y","volume":"13","author":"J Alcal\u00e1-Fdez","year":"2009","unstructured":"Alcal\u00e1-Fdez, J., et al.: KEEL: a software tool to assess evolutionary algorithms for data mining problems. Soft. Comput. 13, 307\u2013318 (2009)","journal-title":"Soft. Comput."},{"issue":"6","key":"24_CR24","doi-asserted-by":"publisher","first-page":"913","DOI":"10.1109\/TEVC.2009.2039140","volume":"14","author":"A Fern\u00e1ndez","year":"2010","unstructured":"Fern\u00e1ndez, A., Garc\u00eda, S., Luengo, J., Bernad\u00f3-Mansilla, E., Herrera, F.: Genetics-based machine learning for rule induction: state of the art, taxonomy, and comparative study. IEEE Trans. Evol. Comput. 14(6), 913\u2013941 (2010)","journal-title":"IEEE Trans. Evol. Comput."},{"key":"24_CR25","first-page":"310","volume":"8","author":"OK Oyebode","year":"2014","unstructured":"Oyebode, O.K., Adeyemo, J.A.: Genetic programming: principles, applications and opportunities for hydrological modelling. World Acad. Sci. Eng. Technol. Int. J. Environ. Ecol. Geol. Min. Eng. 8, 310\u2013316 (2014)","journal-title":"World Acad. Sci. Eng. Technol. Int. J. Environ. Ecol. Geol. Min. Eng."},{"key":"24_CR26","first-page":"819","volume-title":"Advances in Evolutionary Computation","author":"AA Freitas","year":"2002","unstructured":"Freitas, A.A.: A survey of evolutionary algorithms for data mining and knowledge discovery. In: Ghosh, A., Tsutsui, S. (eds.) Advances in Evolutionary Computation, pp. 819\u2013845. Springer, Heidelberg (2002)"},{"key":"24_CR27","doi-asserted-by":"publisher","first-page":"79","DOI":"10.1007\/978-0-387-69935-6_4","volume-title":"Soft Computing for Knowledge Discovery and Data Mining, Part II","author":"AA Freitas","year":"2008","unstructured":"Freitas, A.A.: A review of evolutionary algorithms for data mining. In: Maimon, O., Rokach, L. (eds.) Soft Computing for Knowledge Discovery and Data Mining, Part II, pp. 79\u2013111. Springer, Boston (2008). \nhttps:\/\/doi.org\/10.1007\/978-0-387-69935-6_4"},{"key":"24_CR28","volume-title":"Data Mining: Practical Machine Learning Tools and Techniques","author":"IH Witten","year":"2005","unstructured":"Witten, I.H., Frank, E.: Data Mining: Practical Machine Learning Tools and Techniques, 2nd edn. Morgan Kaufmann, San Francisco (2005)","edition":"2"},{"key":"24_CR29","doi-asserted-by":"publisher","DOI":"10.1017\/CBO9780511973000","volume-title":"Machine Learning: The Art and Science of Algorithms that Make Sense of Data","author":"P Flach","year":"2012","unstructured":"Flach, P.: Machine Learning: The Art and Science of Algorithms that Make Sense of Data. Cambridge University Press, Cambridge (2012)"},{"key":"24_CR30","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-642-02541-9","volume-title":"Automating the Design of Data Mining Algorithms: An Evolutionary Computation Approach","author":"GL Pappa","year":"2010","unstructured":"Pappa, G.L., Freitas, A.A.: Automating the Design of Data Mining Algorithms: An Evolutionary Computation Approach. Springer, Heidelberg (2010). \nhttps:\/\/doi.org\/10.1007\/978-3-642-02541-9"},{"key":"24_CR31","volume-title":"Data Mining: Practical Machine Learning, Tools and Techniques","author":"IH Witten","year":"2011","unstructured":"Witten, I.H., Frank, E., Hall, M.A.: Data Mining: Practical Machine Learning, Tools and Techniques, 3rd edn. Elsevier Inc., Waltham (2011)","edition":"3"},{"key":"24_CR32","series-title":"Lecture Notes in Computer Science (Lecture Notes in Artificial Intelligence)","doi-asserted-by":"publisher","first-page":"291","DOI":"10.1007\/978-3-540-71231-2_20","volume-title":"Learning Classifier Systems","author":"J Bacardit","year":"2007","unstructured":"Bacardit, J., Goldberg, D.E., Butz, M.V.: Improving the performance of a pittsburgh learning classifier system using a default rule. In: Kovacs, T., Llor\u00e0, X., Takadama, K., Lanzi, P.L., Stolzmann, W., Wilson, S.W. (eds.) IWLCS 2003-2005. LNCS (LNAI), vol. 4399, pp. 291\u2013307. Springer, Heidelberg (2007). \nhttps:\/\/doi.org\/10.1007\/978-3-540-71231-2_20"},{"key":"24_CR33","volume-title":"Genetic Algorithms in Search, Optimization and Machine Learning","author":"DE Goldberg","year":"1989","unstructured":"Goldberg, D.E.: Genetic Algorithms in Search, Optimization and Machine Learning. Addison-Wesley, Reading (1989)"},{"key":"24_CR34","unstructured":"Blake, C., Merz, C.: Repository of machine learning databases (UCI). Center for Machine Learning and Intelligent Systems (1998)"},{"issue":"1","key":"24_CR35","doi-asserted-by":"publisher","first-page":"39","DOI":"10.1023\/A:1008280620621","volume":"7","author":"I Kononenko","year":"1997","unstructured":"Kononenko, I., Simec, E., Robnik-Sikonja, M.: Overcoming the myopia of inductive learning algorithms with RELIEFF. Appl. Intell. 7(1), 39\u201355 (1997)","journal-title":"Appl. Intell."},{"key":"24_CR36","series-title":"Lecture Notes in Computer Science","doi-asserted-by":"publisher","first-page":"254","DOI":"10.1007\/978-3-540-45160-0_25","volume-title":"Advances in Web-Age Information Management","author":"J Li","year":"2003","unstructured":"Li, J., Wong, L.: Using rules to analyse bio-medical data: a comparison between C4.5 and PCL. In: Dong, G., Tang, C., Wang, W. (eds.) WAIM 2003. LNCS, vol. 2762, pp. 254\u2013265. Springer, Heidelberg (2003). \nhttps:\/\/doi.org\/10.1007\/978-3-540-45160-0_25"},{"issue":"6","key":"24_CR37","doi-asserted-by":"publisher","first-page":"770","DOI":"10.1109\/TKDE.2004.11","volume":"16","author":"ZH Zhou","year":"2004","unstructured":"Zhou, Z.H., Jiang, Y.: NeC4.5: neural ensemble based C4.5. IEEE Trans. Knowl. Data Eng. 16(6), 770\u2013773 (2004)","journal-title":"IEEE Trans. Knowl. Data Eng."},{"key":"24_CR38","unstructured":"Smirnov, E., Sprinkhuizen-Kuyper, I.G., Nalbantis, I.: Unanimous voting using support vector machines. Technical report, ERIM and Universiteit Rotterdam, IKAT, Universiteit Maastricht (2004)"}],"container-title":["Advances in Intelligent Systems and Computing","Practical Applications of Computational Biology and Bioinformatics, 12th International Conference"],"original-title":[],"link":[{"URL":"http:\/\/link.springer.com\/content\/pdf\/10.1007\/978-3-319-98702-6_24","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2018,8,16]],"date-time":"2018-08-16T05:46:32Z","timestamp":1534398392000},"score":1,"resource":{"primary":{"URL":"http:\/\/link.springer.com\/10.1007\/978-3-319-98702-6_24"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2018,8,17]]},"ISBN":["9783319987019","9783319987026"],"references-count":38,"URL":"https:\/\/doi.org\/10.1007\/978-3-319-98702-6_24","relation":{},"ISSN":["2194-5357","2194-5365"],"issn-type":[{"type":"print","value":"2194-5357"},{"type":"electronic","value":"2194-5365"}],"subject":[],"published":{"date-parts":[[2018,8,17]]}}}