Titlebook: Handbuch Mitarbeiterführung; Wirtschaftspsycholog J?rg Felfe,Rolf van Dick Book 20161st edition Springer-Verlag Berlin Heidelberg 2016 Führ

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n description or other complexities that cause difficulty for the conv- tional approaches of logistic regression, neural network models, and de- sion trees. Among these traditional algorithms, neural network models often have a relative advantage when data is complex. We will discuss methods with si

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Carsten C. Schermulyn description or other complexities that cause difficulty for the conv- tional approaches of logistic regression, neural network models, and de- sion trees. Among these traditional algorithms, neural network models often have a relative advantage when data is complex. We will discuss methods with si

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Catharina Decker,Niels Van Quaquebekes which occur frequently together. Nowadays, data collection is ubiquitous in social and business areas. Many companies and organizations want to do the collaborative association rules mining to get the joint benefits. However, the sensitive information leakage is a problem we have to solve and priv

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Martin Puppatz,Jürgen Dellericy decision-making. Existing models leveraging deep learning with longitudinal healthcare data have demonstrated the benefits of Transformer-based approaches to learning temporal relationships among medical codes (e.g., diagnoses, medications, procedures). Recent applications have also recognised t

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mon deep-learning models for disease prediction. However, it is difficult to fully learn the graphic encounter structure of EHR to improve prediction performance. Moreover, in prediction tasks, chronic kidney disease (CKD) has a poor prognosis due to excessive risk factors and complex comorbidities.

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