private KnowledgeRule createRuleTree(IEnumerable <NodeReference> toCover, MultiTraceLog log)
{
var rule = createBestRule(toCover, log);
if (rule == null)
{
return(null);
}
if (
rule.InitialYesNodes.Count() == 0 ||
rule.InitialNoNodes.Count() == 0
)
{
//current rule doesn't provide any improvement
return(rule);
}
if (!isClassConsistent(rule.InitialNoNodes))
{
rule.AddNoBranch(createRuleTree(rule.InitialNoNodes, log));
}
if (!isClassConsistent(rule.InitialYesNodes))
{
rule.AddYesBranch(createRuleTree(rule.InitialYesNodes, log));
}
return(rule);
}
internal void Retrain()
{
var log = new MultiTraceLog(_knownClassifications.Keys, Knowledge);
Root = createRuleTree(new HashSet <NodeReference>(_knownClassifications.Keys), log);
}
private KnowledgeRule createBestRule(IEnumerable <NodeReference> classifiedNodes, MultiTraceLog log)
{
var bestScore = Double.NegativeInfinity;
TraceNode bestTraceNode = null;
Trace bestTrace = null;
IEnumerable <NodeReference> bestCoverage = null;
//find best classification rule
foreach (var traceNode in log.TraceNodes)
{
var debug = traceNode.ToString();
foreach (var trace in traceNode.Traces)
{
var coverage = trace.InitialNodes;
var currentScore = getClassificationScore(classifiedNodes, coverage, trace);
if (currentScore > bestScore)
{
bestCoverage = coverage;
bestScore = currentScore;
bestTraceNode = traceNode;
bestTrace = trace;
}
}
}
if (bestCoverage == null)
{
return(null);
}
var yesNodes = bestCoverage.Intersect(classifiedNodes);
var noNodes = classifiedNodes.Except(yesNodes);
return(new KnowledgeRule(bestTraceNode.Path, bestTrace.CurrentNode, yesNodes, noNodes));
}