jointly with machine learning tools such as Support Vector Machine, Boosted Regression and Post-LASSO. It carefully selects … taking into account policy goals and budget constraints. Finally, it uses unsupervised machine learning to divide students at …

interactions between them. We illustrate the ability of Machine Learning (ML) methods (Regression Trees, Random Forests and …

sample set. In our opinion, this is a strong indication that the method we propose could provide a viable statistical machine … learning technique for the empirical validation of (large-scale) ABMs. …

. These key features include best linear predictors of the effects using machine learning proxies, average effects sorted by … settings, where the effects are proxied by machine learning methods. We post-process these proxies into the estimates of the … machine learning applications. An empirical application to the impact of micro-credit on economic development illustrates the …