On June 27th, 2006 - we have released new versions of the
HUGIN Graphical User Interface (v6.7) and HUGIN Decision Engine (v6.5).
The main new features of this release are:
Hugin Graphical User Interface v6.7:
The HUGIN Graphical User Interface has been extended with support for
sensitivity to evidence (SE) analysis on discrete random variables in
Bayesian networks and influence diagrams. SE analysis includes determining
minimum and maximum posterior beliefs, impact of evidence analysis,
discrimination between competing hypotheses, what-if analysis, and
sensitivity to findings:
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Determining minimum and maximum beliefs is useful for analysing the
sensitivity of a hypothesis variable relative to an unobserved variable.
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Evidence impact analysis investigates the impact of various subsets of
the evidence on a hypothesis by computing the normalized likelihoods of
the hypothesis given the evidence.
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Discrimination between competing hypotheses is based on the calculation
of Bayes' factor. This analysis supports the identification of subsets
of the evidence which discriminates between two hypotheses.
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What-if analysis investigates the impact of changing the value of an
observed variable on the posterior distribution of a hypothesis
variable.
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Sensitivity to findings analysis analyses the impact a single finding
has on the posterior probability of a hypothesis.
The Value of Information analysis dialog of the HUGIN Graphical User
Interface has been improved with new features:
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The dialog now gives a graphical representation of the mutual
information score between each information variable and the target node.
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The mutual information score between the target and each information
variable is compared to the entropy of the target node.
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The precision of the displayed mutual information score is sensitive to
the selected precision.
The Conflict Resolution dialog of the HUGIN Graphical User Interface has
been improved with a number of new features:
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The dialog now has the option of selecting the set of possible
hypothesis variables.
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The dialog gives a graphical representation of the value of the conflict
measure after resolution for each possible conflict resolution.
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The precision of the displayed conflict measure score is sensitive to
the selected precision.
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It is possible to perform hypothesis driven conflict analysis. This
enables the user to investigate the impact of individual findings on the
posterior probability of the hypothesis.
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Support for tracing the source of a possible conflict has been improved.
The user may compute partial conflicts for all subsets of a selected set
of evidence.
The HUGIN Graphical User Interface has been improved with various new
features. This includes:
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Simulation of chance variables in Run-Mode. This functionality allows
the user to simulate an instantiation of all variables given the
inserted evidence.
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The menu items under the "Network" menu have been rearranged.
An "Analysis" menu item has been introduced.
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Monitors and node lists are now updated immediately after entering a
value on a continuous chance node (as opposed to after the propagation).
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Functionality for reporting the beliefs of a selected node or all nodes
to the Network Log has been included.
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The entropy of a discrete chance node is shown in the Usage Log when the
node is selected in run-mode.
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The mutual information score between two discrete chance nodes is shown
in the Usage Log (in Run Mode only) when selecting their connecting
edge.
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Improved support for long menus (e.g. long menus may appear as a result
of having loaded a large number of classes).
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d-separation analysis is now possible for NetworkModels in edit mode.
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Functionality for rearranging node states has been included.
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Functionality for printing monitor windows with the graph of a model has
been included.
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It is now possible to include monitor windows when writing a model as
BMP.
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It is possible to replace a parent node of a child node without losing
the table of the child in the process.
Finally, efforts have been put into improving the stability of the HUGIN
Graphical User Interface.
Hugin Decision Engine v6.5:
The HUGIN Decision Engine has been extended with the following features:
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Functions for computing the AIC and BIC scores have been included. AIC
and BIC are scores of comparing model quality taking model complexity
into account.
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It is now possible to enter a data case as evidence using a single
function. This is, for instance, useful for iterating over all data
cases and computing posterior beliefs.
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Functions for getting the state index of a discrete chance or decision
node corresponding to a value or a label have been included. This is
particularly useful for inserting evidence on a node with interval
subtype.
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Functionality for performing
d-separation
analysis has been included. This includes two functions for
obtaining the nodes that are d-connected and d-separated to a set nodes,
respectively, given a set of hard and a set of soft evidence.
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Functionality for cloning nodes and domains has been included.
In addition some minor revisions have been made to existing functionality of
the HUGIN Decision Engine:
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The amount of case data which can be handled by the learning algorithms
has been doubled (given the same amount of physical memory).
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The HUGIN API now supports simple labels without quotes in case and data
files (as opposed to requiring labels always to be quoted).
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The EM algorithm reports the AIC and BIC scores to its log file after
completion of parameter estimation.
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Default labels for Boolean nodes have been changed to "false"
and "true" in the HUGIN C API and HUGIN ActiveX server.
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The h_domain_get_log_likelihood function (in the HUGIN C API and
equivalent functions in other HUGIN APIs) now return the log-likelihood
using the actual parameter values (as opposed to using the parameter
values of the penultimate iteration when using EM).