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Information Journal Paper

Title

DIFFERENT FEATURE SELECTION METHODS AND AUDITORS' OPINION TYPE PREDICTION

Pages

  81-102

Abstract

 This research is aimed to investigate and compare the effects of different FEATURE SELECTION METHODS on AUDITORS' OPINION TYPE PREDICTION. To do so, this research compares the performance of FEATURE SELECTION METHODS (including correlation-based, t-test, stepwise discriminate analysis, relief and factor analysis). Two classifiers used in this study are SUPPORT VECTOR MACHINE and NEURAL NETWORKS. The sample includes 1214 firms-years listed in the Tehran Stock Exchange in the period from 2008 to 2015. The results confirm the effectiveness of FEATURE SELECTION METHODS and significant differences among their performance. In other wordsc, using the FEATURE SELECTION METHODS increases the mean of accuracy and reduces type I and type II errors. Furthermore, the results indicate that SUPPORT VECTOR MACHINE outperforms the NEURAL NETWORKS.

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  • Cite

    APA: Copy

    KHAJAVI, SHOKROLLAH, KAZEM NEJAD, MOSTAFA, DEHGHANI SADI, ALI ASGHAR, & MOMTAZIAN, ALIREZA. (2018). DIFFERENT FEATURE SELECTION METHODS AND AUDITORS' OPINION TYPE PREDICTION. JOURNAL OF EMPIRICAL RESEARCH IN ACCOUNTING, 7(27 ), 81-102. SID. https://sid.ir/paper/241048/en

    Vancouver: Copy

    KHAJAVI SHOKROLLAH, KAZEM NEJAD MOSTAFA, DEHGHANI SADI ALI ASGHAR, MOMTAZIAN ALIREZA. DIFFERENT FEATURE SELECTION METHODS AND AUDITORS' OPINION TYPE PREDICTION. JOURNAL OF EMPIRICAL RESEARCH IN ACCOUNTING[Internet]. 2018;7(27 ):81-102. Available from: https://sid.ir/paper/241048/en

    IEEE: Copy

    SHOKROLLAH KHAJAVI, MOSTAFA KAZEM NEJAD, ALI ASGHAR DEHGHANI SADI, and ALIREZA MOMTAZIAN, “DIFFERENT FEATURE SELECTION METHODS AND AUDITORS' OPINION TYPE PREDICTION,” JOURNAL OF EMPIRICAL RESEARCH IN ACCOUNTING, vol. 7, no. 27 , pp. 81–102, 2018, [Online]. Available: https://sid.ir/paper/241048/en

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