Fast Greedy Search (FGES) Algorithm for Discrete Variables
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چکیده
FGESd is an algorithm that takes as input a dataset of discrete variables, greedily searches over selected causal Bayesian network (CBN) structures (models), and outputs the highest scoring model it finds. The model that FGESd returns serves as a data-supported hypothesis about causal relationships that exist among the variables in the dataset. Such models are intended to help scientists form hypotheses and guide the design of experiments to investigate these hypotheses.
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تاریخ انتشار 2017