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parameter uncertainty
An uncertainty is a parameter uncertainty if the range is continuous from the lower bound to the upper bound. A parameter uncertainty can be either real valued or discrete valued.
categorical uncertainty
An uncertianty is categorical if there is not a range but a set of possibilities over wich one wants to sample.
uncertainty space
the space created by the set of uncertainties
a python class responsible for running a series of computational experiments.
model interface
a python class that provides an interface to an underlying model
working directory
a directory that contains files that a model needs
classification trees
a category of machine learning algorithms for rule induction
prim (patient rule induction method)
a rule induction algorithm
a metric developed for scenario discovery
a metric developed for scenario discovery
scenario discovery
a use case of EMA
A case specifies the input parameters for a run of a model. It is a dict instance, with the names of the uncertainties as key, and their sampled values as value.
An experiment is a complete specification for a run. It specifies the case, the name of the policy, and the name of the model.
a policy is by definition an object with a name attribute. So, policy[‘name’] most return the name of the policy
the combination of an experiment and the associated outcomes for the experiment
the data of interest produced by a model given an experiment