{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2024,7,28]],"date-time":"2024-07-28T17:12:48Z","timestamp":1722186768666},"reference-count":28,"publisher":"IGI Global","issue":"1","content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":[],"published-print":{"date-parts":[[2018,1]]},"abstract":"The main goal of this article is to present a statistical study of decision tree learning algorithms based on the measures of different parametric entropies. Partial empirical evidence is presented to support the conjecture that the parameter adjusting of different entropy measures might bias the classification. Here, the receiver operating characteristic (ROC) curve analysis, precisely, the area under the ROC curve (AURC) gives the best criterion to evaluate decision trees based on parametric entropies. The authors emphasize that the improvement of the AURC relies on of the type of each dataset. The results support the hypothesis that parametric algorithms are useful for datasets with numeric and nominal, but not for mixed, attributes; thus, four hybrid approaches are proposed. The hybrid algorithm, which is based on Renyi entropy, is suitable for nominal, numeric, and mixed datasets. Moreover, it requires less time when the number of nodes is reduced, when the AURC is maintaining or increasing, thus it is preferable in large datasets.<\/jats:p>","DOI":"10.4018\/ijdwm.2018010101","type":"journal-article","created":{"date-parts":[[2018,2,1]],"date-time":"2018-02-01T15:26:07Z","timestamp":1517498767000},"page":"1-14","source":"Crossref","is-referenced-by-count":8,"title":["Statistical Entropy Measures in C4.5 Trees"],"prefix":"10.4018","volume":"14","author":[{"given":"Aldo Ramirez","family":"Arellano","sequence":"first","affiliation":[{"name":"Escuela Nacional de Ciencias Biol\u00f3gicas, Instituto Polit\u00e9cnico Nacional, Mexico City, Mexico"}]},{"given":"Juan","family":"Bory-Reyes","sequence":"additional","affiliation":[{"name":"Escuela Superior de Ingenier\u00eda Mec\u00e1nica y El\u00e9ctrica Zacatenco, Instituto Polit\u00e9cnico Nacional, Mexico City, Mexico"}]},{"given":"Luis Manuel","family":"Hernandez-Simon","sequence":"additional","affiliation":[{"name":"Escuela Superior de Ingenier\u00eda Mec\u00e1nica y El\u00e9ctrica Zacatenco, Instituto Polit\u00e9cnico Nacional, Mexico City, Mexico"}]}],"member":"2432","reference":[{"key":"IJDWM.2018010101-0","doi-asserted-by":"publisher","DOI":"10.1016\/S0375-9601(96)00832-8"},{"key":"IJDWM.2018010101-1","doi-asserted-by":"publisher","DOI":"10.1007\/BF01901932"},{"key":"IJDWM.2018010101-2","doi-asserted-by":"publisher","DOI":"10.1080\/00107510902823517"},{"key":"IJDWM.2018010101-3","doi-asserted-by":"publisher","DOI":"10.1080\/00949658908811181"},{"key":"IJDWM.2018010101-4","first-page":"1","article-title":"J. (2006). Statistical Comparisons of Classifiers over Multiple Data Sets.","volume":"7","year":"2006","journal-title":"Journal of Machine Learning Research"},{"key":"IJDWM.2018010101-5","doi-asserted-by":"publisher","DOI":"10.12693\/APhysPolA.129.971"},{"key":"IJDWM.2018010101-6","doi-asserted-by":"publisher","DOI":"10.15439\/2015F121"},{"key":"IJDWM.2018010101-7","doi-asserted-by":"publisher","DOI":"10.1145\/1656274.1656278"},{"key":"IJDWM.2018010101-8","author":"J.Han","year":"2011","journal-title":"Data Mining: Concepts and Techniques"},{"issue":"1","key":"IJDWM.2018010101-9","first-page":"30","article-title":"Quantification method of classification processes. Concept of structural \u03b1-entropy.","volume":"3","author":"J.Havrda","year":"1967","journal-title":"Kybernetika"},{"issue":"12","key":"IJDWM.2018010101-10","first-page":"8","article-title":"An Efficient Modified ID3 Decision Tree Algorithm for Data Mining Using S-T Entropy.","volume":"4","author":"A.Kumar","year":"2014","journal-title":"International Journal of Advanced Research in Computer Science and Software Engineering"},{"key":"IJDWM.2018010101-11","doi-asserted-by":"publisher","DOI":"10.1016\/S0375-9601(98)00500-3"},{"key":"IJDWM.2018010101-12","author":"M.Lichman","year":"2013","journal-title":"UCI Machine Learning Repository. University of California"},{"key":"IJDWM.2018010101-13","doi-asserted-by":"publisher","DOI":"10.5923\/j.ajis.20120205.05"},{"key":"IJDWM.2018010101-14","doi-asserted-by":"publisher","DOI":"10.1109\/ICIMP.2010.23"},{"key":"IJDWM.2018010101-15","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-540-69731-2_62"},{"key":"IJDWM.2018010101-16","doi-asserted-by":"publisher","DOI":"10.7763\/IJIEE.2012.V2.93"},{"key":"IJDWM.2018010101-17","doi-asserted-by":"publisher","DOI":"10.1080\/00949657908810305"},{"key":"IJDWM.2018010101-18","author":"J. R.Quinlan","year":"1993","journal-title":"C4.5: Programs for machine learning"},{"key":"IJDWM.2018010101-19","first-page":"547","article-title":"On measures of entropy and information.","volume":"Vol. 1","author":"A.Renyi","year":"1961","journal-title":"Berkeley Symposium on Mathematical Statistics and Probability"},{"key":"IJDWM.2018010101-20","doi-asserted-by":"publisher","DOI":"10.1002\/j.1538-7305.1948.tb01338.x"},{"key":"IJDWM.2018010101-21","first-page":"28","article-title":"New non-additive measures of entropy for discrete probability distributions.","volume":"10","author":"B. D.Sharma","year":"1975","journal-title":"Journal of Mathematical Sciences"},{"key":"IJDWM.2018010101-22","doi-asserted-by":"publisher","DOI":"10.1007\/BF01899728"},{"key":"IJDWM.2018010101-23","doi-asserted-by":"publisher","DOI":"10.5120\/14249-2444"},{"key":"IJDWM.2018010101-24","unstructured":"Taneja, I. J. (1975). A study of generalized measures in information theory. Unpublished doctoral dissertation, University of Delhi, Delhi."},{"key":"IJDWM.2018010101-25","doi-asserted-by":"publisher","DOI":"10.1007\/BF01016429"},{"key":"IJDWM.2018010101-26","doi-asserted-by":"publisher","DOI":"10.1007\/978-0-387-85359-8_3"},{"key":"IJDWM.2018010101-27","doi-asserted-by":"publisher","DOI":"10.1016\/j.knosys.2016.12.021"}],"container-title":["International Journal of Data Warehousing and Mining"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/www.igi-global.com\/viewtitle.aspx?TitleId=198971","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2022,5,6]],"date-time":"2022-05-06T09:50:24Z","timestamp":1651830624000},"score":1,"resource":{"primary":{"URL":"http:\/\/services.igi-global.com\/resolvedoi\/resolve.aspx?doi=10.4018\/IJDWM.2018010101"}},"subtitle":[""],"short-title":[],"issued":{"date-parts":[[2018,1]]},"references-count":28,"journal-issue":{"issue":"1"},"URL":"https:\/\/doi.org\/10.4018\/ijdwm.2018010101","relation":{},"ISSN":["1548-3924","1548-3932"],"issn-type":[{"value":"1548-3924","type":"print"},{"value":"1548-3932","type":"electronic"}],"subject":[],"published":{"date-parts":[[2018,1]]}}}