Interface Inference

    • Method Detail

      • getNetwork

        Network getNetwork()
        The target Bayesian network.
      • getQueryDistributions

        QueryDistributionCollection getQueryDistributions()
        Gets the collection of distributions to calculate. See QueryDistributionCollection. If required, a query distribution collection can be dynamically attached or detached. Also note that individual elements can be enabled or disabled on a per query basis.
      • setQueryDistributions

        void setQueryDistributions​(QueryDistributionCollection value)
        Sets the collection of distributions to calculate. See QueryDistributionCollection. If required, a query distribution collection can be dynamically attached or detached. Also note that individual elements can be enabled or disabled on a per query basis.
      • getQueryFunctions

        QueryFunctionCollection getQueryFunctions()
        Gets the collection of functions to evaluate, after QueryDistributions have been calculated. If required, a query function collection can be dynamically attached or detached. Also note that individual elements can be enabled or disabled on a per query basis.
      • setQueryFunctions

        void setQueryFunctions​(QueryFunctionCollection value)
        Sets the collection of functions to evaluate, after QueryDistributions have been calculated. If required, a query function collection can be dynamically attached or detached. Also note that individual elements can be enabled or disabled on a per query basis.
      • query

        void query​(QueryOptions queryOptions,
                   QueryOutput queryOutput)
            throws InconsistentEvidenceException
        Calculates a number of distributions, e.g. P(A) and P(B) given the evidence (case data, e.g. row in a database), and if requested the log-likelihood of the data. Each time this method is called the distributions have their values replaced, acting like buffers.

        As well as requesting distributions of the form P(A), P(B) it is also possible to request distributions over a number of variables such as P(A,B).

        If CLGaussian distributions are requested that include instantiated discrete variables, an algorithm may legitimately return mean and covariance values equal to NaN for entries corresponding to inconsistent discrete combinations. For example, if a CLGaussian is requested that includes a discrete variable 'Gender' with states 'Male' and 'Female' and evidence is set to 'Female' then any mean and covariance entries that correspond to 'Male' may be set to NaN. NaN values will always be accompanied by a corresponding zero value in the CLGaussian.getTable().

        Parameters:
        queryOptions - Options governing which calculations are performed and how.
        queryOutput - Returns any information, in addition to the distributions, that is requested. For example the log-likelihood.
        Throws:
        InvalidNetworkException - Raised if the network is invalid.
        InconsistentEvidenceException - Raised if inconsistent evidence is detected, or underflow/overflow occurs when calculating queries or the conflict measure. Note that log-likelihood calculations do not raise this exception, but instead report -Infinity or +Infinity.
      • getQueryLifecycle

        QueryLifecycle getQueryLifecycle()
        Optional, allowing callers to hook into query lifecycle events, such as begin query and end query.
      • setQueryLifecycle

        void setQueryLifecycle​(QueryLifecycle value)
        Optional, allowing callers to hook into query lifecycle events, such as begin query and end query.