Index
$#! · 0-9 · A · B · C · D · E · F · G · H · I · J · K · L · M · N · O · P · Q · R · S · T · U · V · W · X · Y · Z
A
 About
B
 Build and Propagate
 Build And Propagate
C
 ClassCollection
 ClassList
D
 Domain
E
 Expressions
L
 Library Setup
 License
 Load and Propagate
 Load And Propagate
M
 Model
N
 NET, Differences from
 Net Construction Sample
 NetworkModel
 Node Naming Scheme for oobn
O
 Overloads
S
 Sequential Learning
T
 Table
This library makes tools available in vba to easily access the HUGIN decision engine.
This example describes how a Bayesian network can be constructed using the HUGIN vba API.
ParseClasses(String, ClassParseListener)
Contains(Class)
Triangulate(Domain.TriangulationMethod)
All overloaded expressions are currently given a number after their name, e.g.
The 32 and 64 bit versions of hugin each contain 4 libraries for vba.
The HUGIN vba API and the HUGIN decision engine are copyright HUGIN EXPERT A/S.
This example is used to load a Bayesian network or a LIMID.
SetExpression(vba_size_t, Expression)
The primary differences between the .NET API and the vba API are that the vba API uses the HVBA class instead of constructors and that it does not contain any overloaded methods.
This example shows a way to build a simple network with the vba API.
OpenLogFile(String)
When creating a runtime domain from a Class, all nodes are named by concatenating the names of the nodes in the list of source nodes(for source nodes see GetSource()) using a dot character(‘.’
This page contains a list of all overloaded methods, their new names and inputs.
This example presents a skeleton for sequential learning.
GetData()
Close