public bool IsTrueFor(double probability,
Dictionary <string, bool?> modelBuiltUpSoFar)
{
Dictionary <string, bool?> conditions = new Dictionary <string, bool?>();
if (this.IsRoot())
{
conditions[Variable] = true;
}
else
{
for (int i = 0; i < this.Parents.Count; i++)
{
BayesNetNode parent = this.Parents[i];
conditions[parent.Variable] = modelBuiltUpSoFar[parent.Variable];
}
}
double trueProbability = this.ProbabilityOf(conditions);
if (probability <= trueProbability)
{
return(true);
}
return(false);
}
public void InfluencedBy(BayesNetNode parent1, BayesNetNode parent2)
{
this.InfluencedBy(parent1);
this.InfluencedBy(parent2);
distribution = new ProbabilityDistribution(parent1.Variable,
parent2.Variable);
}
private void AddChild(BayesNetNode node)
{
if (!(this.Children.Contains(node)))
{
this.Children.Add(node);
}
}
private void AddParent(BayesNetNode node)
{
if (!(this.Parents.Contains(node)))
{
this.Parents.Add(node);
}
}
public bool Equals(BayesNetNode other)
{
if (ReferenceEquals(null, other))
{
return(false);
}
if (ReferenceEquals(this, other))
{
return(true);
}
return(Equals(other.Variable, this.Variable));
}
public double ProbabilityOf(string Y, bool?value,
Dictionary <string, bool?> evidence)
{
BayesNetNode y = this.GetNodeOf(Y);
if (y == null)
{
throw new ApplicationException("Unable to find a node with variable "
+ Y);
}
IList <BayesNetNode> parentNodes = y.Parents;
if (parentNodes.Count == 0) // root nodes
{
Dictionary <string, bool?> yTable = new Dictionary <string, bool?>();
yTable[Y] = value;
double prob = y.ProbabilityOf(yTable);
return(prob);
}
else // non rootnodes
{
Dictionary <string, bool?> parentValues = new Dictionary <string, bool?>();
foreach (BayesNetNode parent in parentNodes)
{
parentValues[parent.Variable] = evidence[parent.Variable];
}
double prob = y.ProbabilityOf(parentValues);
if (value.Equals(true))
{
return(prob);
}
return(1.0 - prob);
}
}
private IList <BayesNetNode> MarkovBlanket(BayesNetNode node,
IList <BayesNetNode> soFar)
{
// parents
IList <BayesNetNode> parents = node.Parents;
foreach (BayesNetNode parent in parents)
{
if (!soFar.Contains(parent))
{
soFar.Add(parent);
}
}
// children
IList <BayesNetNode> children = node.Children;
foreach (BayesNetNode child in children)
{
if (!soFar.Contains(child))
{
soFar.Add(child);
IList <BayesNetNode> childsParents = child.Parents;
foreach (BayesNetNode childsParent in childsParents)
{
;
if ((!soFar.Contains(childsParent)) &&
(!(childsParent.Equals(node))))
{
soFar.Add(childsParent);
}
} // childsParents
} // end Contains child
} // end child
return(soFar);
}
private IList <BayesNetNode> MarkovBlanket(BayesNetNode node)
{
return(this.MarkovBlanket(node, new List <BayesNetNode>()));
}
public BayesNet(BayesNetNode root1, BayesNetNode root2, BayesNetNode root3) : this(root1, root2)
{
roots.Add(root3);
}
public BayesNet(BayesNetNode root1, BayesNetNode root2) : this(root1) {
roots.Add(root2);
}
public BayesNet(BayesNetNode root)
{
roots.Add(root);
}
public void InfluencedBy(BayesNetNode parent1)
{
this.AddParent(parent1);
parent1.AddChild(this);
distribution = new ProbabilityDistribution(parent1.Variable);
}