Decision trees

Srour, F. Jordan

dc.contributor.author	Srour, F. Jordan
dc.date.accessioned	2026-01-20T13:44:18Z
dc.date.available	2026-01-20T13:44:18Z
dc.date.copyright	2026	en_US
dc.date.issued	2026
dc.identifier.uri	http://hdl.handle.net/10725/17516
dc.description.abstract	This entry describes the value of and methods for using decision trees within the social sciences. An overview of the basic theory behind decision trees coupled with a summary of binary, multi-way, robust, and optimal decision tree algorithms support social scientists in the use of these supervised machine learning tools for both exploratory and predictive analytic contexts.	en_US
dc.language.iso	en	en_US
dc.publisher	Elsevier Inc.	en_US
dc.subject	Decision trees	en_US
dc.subject	Algorithmics	en_US
dc.subject	Trees (Graph theory)	en_US
dc.subject	Machine learning	en_US
dc.subject	Regression analysis	en_US
dc.title	Decision trees	en_US
dc.type	Book / Chapter of a Book	en_US
dc.author.school	AKSOB	en_US
dc.author.idnumber	201204645	en_US
dc.author.department	Department of Information Technology And Operations Management	en_US
dc.keywords	Predictive analytics	en_US
dc.keywords	Supervised machine learning	en_US
dc.keywords	White-box models	en_US
dc.keywords	Classification and regression trees	en_US
dc.keywords	Robust decision trees	en_US
dc.description.bibliographiccitations	Includes bibliographical references	en_US
dc.identifier.doi	https://doi.org/10.1016/B978-0-443-26629-4.00142-8	en_US
dc.identifier.ctation	Srour, F. J. (Forthcoming). Decision trees. In Encyclopedia of Measurement in Social Sciences, 2nd edition (pp. 1-12). Elsevier.	en_US
dc.author.email	jordan.srour@lau.edu.lb	en_US
dc.identifier.tou	http://libraries.lau.edu.lb/research/laur/terms-of-use/articles.php	en_US
dc.note	Chapter from the book: Encyclopedia of Measurement in Social Sciences, 2nd edition.	en_US
dc.publication.date	2026	en_US
dc.author.affiliation	Lebanese American University	en_US
dc.orcid.id2	https://orcid.org/0000-0001-7623-723X	en_US