temporal aggregation. Against this background, this paper introduces two novel approaches based on machine learning and … machine learning and probabilistic prediction models are built by analysing a unique data set of more than 100 million events … timestamp for arriving at that location is estimated. The machine learning model uses artificial neural networks and mixture …

new Machine Learning-based proxy means test (ML-based PMT) to identify the poorest households and field-tested it in … developed our new ML-based PMT by applying machine learning techniques to the nationally-representative 2016-2017 Ghana Living …

We study the economics and finance scholars' reaction to the 2008 financial crisis using machine learning language …

operate. The undisputed predictive power of machine learning (ML) models often plays a crucial role in the 'disruption' of …

genetic algorithm and five forecasting approaches based on machine learning methods. The algorithm was able to select 14 …

. For this purpose, we make predictions with common statistical methods (OLS, Logit) and machine learning (ML) methods. The …

FinTech start-ups over the period 2000-2016. We employ machine learning techniques to classify a large global sample of patent …