Probabilistic Metric Spaces for Privacy by Design Machine Learning Algorithms: Modeling Database Changes
Vicenç Torra, Guillermo Navarro‐Arribas · Lecture notes in computer science · 2018
Machine learning, data mining and statistics are used to analyze the data and to build models from them. Data privacy for big data needs to find a compromise between data analysis and disclosure risk. Privacy by design machine learning algorithms need to take into account the space of models and the relationship between the data that generates the models and the models themselves. In this paper we propose the use of probabilistic metric spaces for comparing these models.