作者: Dominik Paprotny , Oswaldo Morales-Nápoles , Daniël T.H. Worm , Elisa Ragno
DOI: 10.1016/J.SOFTX.2020.100588
关键词:
摘要: Abstract Bayesian Networks (BNs) are probabilistic, graphical models for representing complex dependency structures. They have many applications in science and engineering. Their particularly powerful variant – Non-Parametric BNs the first time implemented as an open-access scriptable code, form of a MATLAB toolbox “BANSHEE”. 1 The software allows quantifying BN, validating underlying assumptions model, visualizing network its corresponding rank correlation matrix, finally making inference with BN based on existing or new evidence. We also include toolbox, discuss paper, some applied published most recent scientific literature.