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 …

develops a model and solution approach for solving the patient bed-assignment problem that is based on a machine learning (ML …

. Basically, the approach consists of an optimization algorithm that interacts with a machine learning model that combines multi …

with a high level of accuracy. Because machine learning methods can model relationships between explanatory and dependent … variables based on complex, non-linear, and/or non-parametric structures, it is not surprising that machine learning approaches … market, comparing different modeling approaches. We apply random forest and neural networks as representatives of machine …

The most promising standard machine learning methods can deliver highly accurate classification results, often … results more interpretable, while Interactive Machine Learning integrates humans into the process of insight discovery. The … Machine Learning (XIL) is embedded in a generalizable Action Design Research (ADR) process – called XIL-ADR. This approach can …