/// <summary>
/// 相当于原项目的Sij（s->i, t->j）。
/// 暂时为最大似然估计。未考虑worker bias。
/// 训练。
/// </summary>
/// <param name="t">t</param>
/// <param name="groupindex">组号</param>
/// <returns></returns>
public double Pr_t_s(TargetLabeltruth t, int groupindex)
{
double numerator = 0;
double denominator = 0;
if (this.AccordedSentenceList.Count != 0)
{
//遍历与此Srouce Labeltruth对应的Sentence List（与分组无关）
foreach (Sentence sentence in this.AccordedSentenceList)
{
//此sentence被标过的target annotation（与分组有关）
foreach (TargetAnnotation targetAnnotation in sentence.TargetWorkerTargetAnnotationDicGroup[groupindex].Values)
{
//被标次数
++denominator;
//此target annotation里含有要找的target label truth
if (targetAnnotation.AccordingWithTargetLabeltruth(t))
{
++numerator;
}
}
}
return(numerator / denominator);
//return Math.Pow(numerator / denominator, ProbabilityConstant.Pr_t[t]);
}
else
{
return(0);
}
}
/// <summary>
/// s转移到t的概率矩阵。
/// （s已知，求t的概率）。
/// 验证和是1。
/// </summary>
/// <returns>s->t->概率</returns>
static public void Pr_t_s(int groupindex)
{
//初始化
CascadedConstant.Pr_t_s = new Dictionary <SourceLabeltruth, IDictionary <TargetLabeltruth, double> >();
//开始直接取
foreach (Label sourceLabel in Constant.SourceTaxonomy.LabelArray)
{
SourceLabeltruth sourceTrue = new SourceLabeltruth(sourceLabel, true);
SourceLabeltruth sourceFalse = new SourceLabeltruth(sourceLabel, false);
CascadedConstant.Pr_t_s.Add(sourceTrue, new Dictionary <TargetLabeltruth, double>());
CascadedConstant.Pr_t_s.Add(sourceFalse, new Dictionary <TargetLabeltruth, double>());
foreach (Label targetLabel in Constant.TargetTaxonomy.LabelArray)
{
TargetLabeltruth targetTrue = new TargetLabeltruth(targetLabel, true);
TargetLabeltruth targetFalse = new TargetLabeltruth(targetLabel, false);
#region 在SourceLabeltruth内计算
CascadedConstant.Pr_t_s[sourceTrue].Add(targetTrue, sourceTrue.Pr_t_s(targetTrue, groupindex));
CascadedConstant.Pr_t_s[sourceTrue].Add(targetFalse, sourceTrue.Pr_t_s(targetFalse, groupindex));
CascadedConstant.Pr_t_s[sourceFalse].Add(targetTrue, sourceFalse.Pr_t_s(targetTrue, groupindex));
CascadedConstant.Pr_t_s[sourceFalse].Add(targetFalse, sourceFalse.Pr_t_s(targetFalse, groupindex));
#endregion
#region normalize(用Pt做指数的话需要，已废弃)
//double trueProbability = sourceTrue.Pr_t_s(targetTrue);
//double falseProbability = sourceTrue.Pr_t_s(targetFalse);
//double constant = trueProbability + falseProbability;
//ProbabilityConstant.Pr_t_s[sourceTrue].Add(targetTrue, trueProbability / constant);
//ProbabilityConstant.Pr_t_s[sourceTrue].Add(targetFalse, falseProbability / constant);
//trueProbability = sourceFalse.Pr_t_s(targetTrue);
//falseProbability = sourceFalse.Pr_t_s(targetFalse);
//constant = trueProbability + falseProbability;
//ProbabilityConstant.Pr_t_s[sourceFalse].Add(targetTrue, trueProbability / constant);
//ProbabilityConstant.Pr_t_s[sourceFalse].Add(targetFalse, falseProbability / constant);
#endregion
}
}
}
