In this article, a new kind of interpretable machine learning method is presented, which can help to understand the … underlying statistical or machine learning model more trustworthy. Basically, real data points (or specific points of interest …

AI and machine learning – and have their own agendas in terms of problem setting, assumptions, and criteria of success …

Hyperparameter tuning is one of the most time-consuming parts in machine learning. Despite the existence of modern …. Usually a resampling technique is used, where the machine learning method has to be fitted a fixed number of k times on …

Previous work in the literature on regional economic integration has proposed the use of machine learning algorithms to …

, and allocate resources. Machine learning (ML) can leverage a patient’s complete health history to make informed decisions …

machine learning techniques in the field of production planning and control has unlocked new opportunities, in both academia …, machine learning techniques offer the opportunity to gain valuable and accurate insights about production processes. However …, machine learning-based approaches for the prediction of delivery dates have not received sufficient attention. Thus, this …

With the increased use of machine learning (ML) models within automated decision-making systems, the demands on the …

The research presents the development and test of a machine learning (ML) model to assess the subjective well-being of …