analysis has traditionally been conducted through human coding, machine learning techniques now enable automated analyses. One … electronic negotiations and how predictive machine learning models react to the successive increase of negotiation data …

data as input and providing it to state-of-the-art machine learning models capable of approximating arbitrary functional … forecast horizon extends. Lastly, we show that the influence of interactions and non- linearities on the machine learning …

well as complementary tools, such as cloud‐based platforms, machine learning algorithms, and econometric approaches. Our …

obtained with the machine learning models, it is possible not only to predict with greater precision who could fall into work … employability are considered: unemployed and discouraged, and the classification of these groups is characterized using machine … learning models and sociodemographic variables, such as educational level, sex, age, marital status, number of children …

This paper examines the prediction of IPO withdrawal using machine learning methods (lasso and random forest) and …

range of individual characteristics, we employ machine learning techniques for variable selection. Our findings show that …