Causal methods present unique challenges compared to traditional machine learning and statistics ... ll start with basic motivations behind causal thinking and a comprehensive introduction to Pearlian ...

Department of Chemical and Biological Engineering, University of Wisconsin, Madison, Wisconsin 53706, United States Department of Materials Science and Engineering, University of Wisconsin, Madison, ...

Multiple machine learning algorithms were tested, and the combination of XGBoost and Instance Hardness Threshold models displayed the best predictive performance. The SHapley Additive exPlanations ...

These applications include the management of infectious diseases, in which machine learning has created inroads in clinical microbiology, radiology, genomics, and the analysis of electronic health ...

In this paper, we develop a machine-learning based approach by formulating a smoothed version of the weight setting problem and using gradient descent in the PyTorch framework to derive approximate ...