Optimization in BayesiaLab

Optimization in BayesiaLab

BayesiaLab’s ability to perform inference across all possible states of all nodes in the network permits searching for optimum target values. BayesiaLab’s Target Dynamic Profile and Target Optimizationfunctions provide a robust toolset for this purpose.

These algorithms can also be used with Direct Effects, BayesiaLab built-in Likelihood Matching algorithm, which allows searching for the optimum combination of correlated drivers. A typical example would be searching for the optimum mix of marketing instruments. BayesiaLab’s Target Optimization will search — within the resource constraints set by the analyst — for those scenarios that optimize the target criterion.

Relevant case studies:




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