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Agenzia delle Entrate e Ministero dell’Economia e delle Finanze (2018). Convenzione triennale per gli esercizi 2018-2020 [Online]. Available at: https://www.finanze.it/export/sites/finanze/.galleries/Documenti/Varie/DF_CONVENZIONE-MEF_ADE_2018.2020_FIRMATA-28_11_2018.pdf.

Allingham, M.G. and Sandmo, A. (1972). Income tax evasion: A theoretical analysis. Journal of Public Economics, I, 323–338.

Barone, M., Pisani, S., Spingola, A. (2017). Data mining application issues in income indicators audits. Argomenti di discussione – Agenzia delle Entrate, 2.

Basta, S., Fassetti, F., Guarascio, M., Manco, G., Giannotti, F., Pedreschi, D., Spinsanti, L., Papi, G., Pisani, S. (2009). High quality true positive prediction for fiscal fraud detection to regressive conditional. 2009 IEEE International Conference on Data Mining Workshops.

Bonchi, F., Giannotti, F., Mainetto, G., Pedreschi, D. (1999). A classification-based methodology for planning auditing strategies in fraud detection. Proc. of SIGKDD99, 175–184.

Breiman, L. (1996). Bagging predictors. Machine Learning, 24(2), 123–140.

Corte dei Conti (2016). Il sistema della riscossione dei tributi erariali al 2015. Deliberazione 20 ottobre 2016, 11/2016/G.

Gonzalez, P.C. and Velasquez, J.D. (2013). Characterization and detection of taxpayers with false invoices using data mining techniques. Expert Systems with Applications, 40(5), 1427–1436.

OpenStax (2013). Introductory Statistics. OpenStax, 19 September [Online]. Available at: http://cnx.org/content/col11562/latest/.

Phua, C., Lee, V., Smith, K., Gayler, R. (2005). A comprehensive survey of data mining-based fraud detection research. Artificial Intelligence Review, submitted.

de Roux, D., Perez, B., Moreno, A., del Pilar Villamil, M., Figueroa, C. (2018). Tax fraud detection for under-reporting declarations using an unsupervised machine learning approach. KDD 2018, 215–222.

de Sisti, P. and Pisani, S. (2007). Data mining e analisi del rischio di frode fiscale: il caso dei crediti d’imposta. Documenti di lavoro dell’Ufficio Studi – Agenzia delle Entrate, 4.

Wu, R., Ou, C.S., Lin, H., Chang, S., Yen, D. (2012). Using data mining technique to enhance tax evasion detection performance. Expert Systems with Applications, 39, 8769–8777.

1 1 A tax notice is a formal written act through which tax authorities assess a higher due taxable income with respect to the declared one.

2 2 Data analyses are performed using WEKA – the data mining workbench developed at Waikato University in Hamilton, New Zealand, released under the GNU GPL license.

3 3 The IRA sent a total of 59,269 tax notices concerning fiscal year 2012 to self-employed individuals allowed to keep simplified registers, so we can manage a quite significant sample.

Chapter written by Mauro BARONE, Stefano PISANI and Andrea SPINGOLA.