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

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

Institution and School/Department of submitter: ΤΕΙ Θεσσαλονίκης
Keywords: Ελεγκτική διαδικασία;Decision trees;Δέντρα επιλογής;SVM;Επιλογή ελεγκτή;Έλεγχοι;Auditor choice;Audit quality;Audit procedure;Audits;Ποιότητα ελέγχου;C4.5;MLP
Issue Date: Aug-2008
Publisher: IOS Press
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: (Ανακτήθηκε 30 Ιουνίου 2015).
Journal: Journal of Computational Methods in Sciences and Engineering Impact Factor & Information, vol. 08, no. 3, 2008
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.
Description: Δημοσιεύσεις μελών--ΣΔΟ--Τμήμα Λογιστική, 2008
ISSN: 1472-7978
Other Identifiers:
Item type: other
Submission Date: 2018-02-27T18:50:59Z
Item language: el
Item access scheme: free
Institution and School/Department of submitter: ΤΕΙ Θεσσαλονίκης
Appears in Collections:Δημοσιεύσεις σε Περιοδικά

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