Detecting Types of Non-Compliance in Personal Income Tax Returns: Analysing Supervised and Unsupervised Algorithms

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Keywords	Tax authorities, Tax fraud, Fraud detection, Non-compliance detection, Fairness, Transparency, Machine learning techniques
Thesis Advisor	Margolin, Max, Eskenazi, P.I.
Persistent URL	hdl.handle.net/2105/57502
Series	Business Analytics & Management
Organisation	Rotterdam School of Management
Citation APA Style AAA Style APA Style Cell Style Chicago Style Harvard Style IEEE Style MLA Style Nature Style Vancouver Style American-Institute-of-Physics Style Council-of-Science-Editors Style BibTex Format Endnote Format RIS Format CSL Format DOIs only Format	Huurman, Tirza. (2021, July 15). Detecting Types of Non-Compliance in Personal Income Tax Returns: Analysing Supervised and Unsupervised Algorithms. Business Analytics & Management. Retrieved from http://hdl.handle.net/2105/57502

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