Titlebook: Machine Learning and Principles and Practice of Knowledge Discovery in Databases; International Worksh Irena Koprinska,Paolo Mignone,Sepide

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Privacy-Preserving Machine Learning in?Life Insurance Risk Predictionm in three general, but plausible Use Cases involving the prediction of insurance claims within a 1-year horizon. Our preliminary experiments suggest that discretization and encryption have negligible impact in the accuracy of ML models.

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Financial Distress Model Prediction Using Machine Learning: A Case Study on?Indonesia’s Consumers Cytree, logistic regression, LightGBM, and the k-nearest neighbor algorithms. The overall accuracy of the proposed model ranged from 0.60 to 0.87, which improved on using the one-year prior growth data of financial attributes.

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Conference proceedings 2023earning and Principles and Practice of Knowledge Discovery in Databases, ECML PKDD 2022, held in Grenoble, France, during September 19–23, 2022.?.The 73 revised full papers and 6 short papers presented in this book were carefully reviewed and selected from 143 submissions. ECML PKDD 2022 presents th

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1865-0929 Machine Learning and Principles and Practice of Knowledge Discovery in Databases, ECML PKDD 2022, held in Grenoble, France, during September 19–23, 2022.?.The 73 revised full papers and 6 short papers presented in this book were carefully reviewed and selected from 143 submissions. ECML PKDD 2022 p

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https://doi.org/10.1007/978-3-031-23633-4artificial intelligence; classification methods; computer crime; computer networks; computer security; co

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978-3-031-23632-7The Editor(s) (if applicable) and The Author(s), under exclusive license to Springer Nature Switzerl