C4.5: programs for machine learning
C4.5: programs for machine learning
Machine learning, neural and statistical classification
Machine learning, neural and statistical classification
Machine Learning
Fast training of support vector machines using sequential minimal optimization
Advances in kernel methods
Data mining: concepts and techniques
Data mining: concepts and techniques
Data Mining techniques for the detection of fraudulent financial statements
Expert Systems with Applications: An International Journal
Selective costing voting for bankruptcy prediction
International Journal of Knowledge-based and Intelligent Engineering Systems
Expert Systems with Applications: An International Journal
Comparing data mining classifiers for grading raisins based on visual features
Computers and Electronics in Agriculture
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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.