Support vector machines, decision trees and neural networks for auditor selection

Support vector machines, decision trees and neural networks for auditor selection

Kirkos, Efstathios/ Spathis, Charalambos/ Manolopoulos, Yannis/ Σπαθής, Χαράλαμπος/ Μανωλόπουλος, Γιάννης/ Κύρκος, Ευστάθιος

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DC Field	Value	Language
dc.contributor.author	Kirkos, Efstathios	el
dc.contributor.author	Spathis, Charalambos	el
dc.contributor.author	Manolopoulos, Yannis	el
dc.contributor.other	Σπαθής, Χαράλαμπος	el
dc.contributor.other	Μανωλόπουλος, Γιάννης	el
dc.contributor.other	Κύρκος, Ευστάθιος	el
dc.date.accessioned	2015-06-30T11:45:14Z	el
dc.date.accessioned	2018-02-27T18:49:59Z	-
dc.date.available	2015-06-30T11:45:14Z	el
dc.date.available	2018-02-27T18:49:59Z	-
dc.date.issued	2008-08	el
dc.identifier	http://www.researchgate.net/publication/262296794_Support_vector_machines_Decision_Trees_and_Neural_Networks_for_auditor_selection	el
dc.identifier.citation	Kirkos, E., Spathis, C. & Manolopoulos, Y. (8 Δεκεμβρίου 2014). Support vector machines, Decision Trees and Neural Networks for auditor selection. Journal of Computational Methods in Sciences and Engineering Impact Factor & Information 8(3). Διαθέσιμο σε: http://www.researchgate.net/publication/262296794_Support_vector_machines_Decision_Trees_and_Neural_Networks_for_auditor_selection (Ανακτήθηκε 30 Ιουνίου 2015).	el
dc.identifier.citation	Journal: Journal of Computational Methods in Sciences and Engineering Impact Factor & Information, vol. 08, no. 3, 2008	el
dc.identifier.issn	1472-7978	el
dc.identifier.uri	http://195.251.240.227/jspui/handle/123456789/5343	-
dc.description	Δημοσιεύσεις μελών--ΣΔΟ--Τμήμα Λογιστική, 2008	el
dc.description.abstract	The selection of a proper auditor is driven by several factors. Here, we use three data mining classification techniques to predict the auditor choice. The methods used are Decision Trees, Neural Networks and Support Vector Machines. The developed models are compared in term of their performances. The wrapper feature selection technique is used for the Decision Tree model. Two models reveal that the level of debt is a factor that influences the auditor choice decision. This study has implications for auditors, investors, company decision makers and researchers.	el
dc.format.extent	148Kb	el
dc.language.iso	en	el
dc.publisher	IOS Press	el
dc.rights	Attribution-NonCommercial-ShareAlike 3.0 Greece	el
dc.rights	Αναφορά Δημιουργού-Μη Εμπορική Χρήση-Παρόμοια Διανομή 3.0 Ελλάδα	el
dc.source.uri	http://www.researchgate.net/journal/1472-7978_Journal_of_Computational_Methods_in_Sciences_and_Engineering	el
dc.subject	Ελεγκτική διαδικασία	el
dc.subject	Decision trees	el
dc.subject	Δέντρα επιλογής	el
dc.subject	SVM	el
dc.subject	Επιλογή ελεγκτή	el
dc.subject	Έλεγχοι	el
dc.subject	Auditor choice	el
dc.subject	Audit quality	el
dc.subject	Audit procedure	el
dc.subject	Audits	el
dc.subject	Ποιότητα ελέγχου	el
dc.subject	C4.5	el
dc.subject	MLP	el
dc.subject.lcsh	Support vector machines	el
dc.subject.lcsh	Trees (Graph theory)	el
dc.subject.lcsh	Δέντρα (Θεωρία γραφικής παράστασης)	el
dc.subject.lcsh	Διαχείριση πηγών πληροφόρησης	el
dc.subject.lcsh	Εξόρυξη δεδομένων	el
dc.subject.lcsh	Information resources management	el
dc.subject.lcsh	Data mining	el
dc.subject.lcsh	Μηχανές διανυσματικής υποστήριξης	el
dc.subject.lcsh	Auditing--Databases	el
dc.subject.lcsh	Ελεγκτική--Βάσεις δεδομένων	el
dc.title	Support vector machines, decision trees and neural networks for auditor selection	el
dc.type	Article	el
heal.type	other	el
heal.type.en	Other	en
heal.dateAvailable	2018-02-27T18:50:59Z	-
heal.language	el	el
heal.access	free	el
heal.recordProvider	ΤΕΙ Θεσσαλονίκης	el
heal.fullTextAvailability	true	el
heal.type.el	Άλλο	el
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Support vector machines, decision trees and neural networks for auditor selection

Kirkos, Efstathios/ Spathis, Charalambos/ Manolopoulos, Yannis/ Σπαθής, Χαράλαμπος/ Μανωλόπουλος, Γιάννης/ Κύρκος, Ευστάθιος