machine learning and deep learning models are applied to selected parameters from an existing household survey data set. In … addition, the deep learning sequential neural networks outperformed all machine learning models achieving an accuracy between …

In this paper we discuss the use and potential advantages and disadvantages of machine learning driven models in rental … machine learning outperform existing and established routines. We make use of data from the Munich rental guide and mainly …

Recent empirical evidence indicates that bond excess returns can be predicted using machine learning models. However …, although the predictive power of machine learning models is intriguing, they typically lack transparency. This paper introduces … produced by machine learning models and recognizes how these determinants relate to bond excess returns. This approach …

Machine learning systems have gained widespread adoption across various industries. This includes highly regulated ones …

between prediction accuracy rates, which are obtained by seven different machine learning algorithms and Corruption Perception …-edge machine learning and deep learning techniques in future studies. There are very few studies which try to explain factors … successful predictions can be made using machine learning algorithms in countries with relatively lower CPI scores. Originality …

This paper sheds new light on the role of communication for cartel formation. Using machine learning to evaluate free …