本文整理汇总了C++中QueryData::nquery方法的典型用法代码示例。如果您正苦于以下问题：C++ QueryData::nquery方法的具体用法？C++ QueryData::nquery怎么用？C++ QueryData::nquery使用的例子？那么, 这里精选的方法代码示例或许可以为您提供帮助。您也可以进一步了解该方法所在类QueryData的用法示例。
在下文中一共展示了QueryData::nquery方法的1个代码示例，这些例子默认根据受欢迎程度排序。您可以为喜欢或者感觉有用的代码点赞，您的评价将有助于系统推荐出更棒的C++代码示例。
示例1: learn
void AdaRanker::learn(const QueryData &data, const Metric &metric)
{
weakRankerWeights = std::vector<double>(data.nfeature(), 0.0);
std::vector<int> weakRankerChecked(data.nfeature(), 0);
// precompute weak rankers
std::vector<std::vector<double> > weakRankerScores(data.nquery(), std::vector<double>(data.nfeature(), 0.0));
for(int q = 0; q < data.nquery(); q++)
{
for(int f = 0; f < data.nfeature(); f++)
{
weakRankerScores[q][f] = metric.measure(weakRank(data.getQuery(q), f));
}
}
// a log of ranker scores
std::vector<double> scores(1, metric.measure(rank(data)));
// iterate over each feature
std::vector<double> queryWeights(data.nquery(), 1.0/data.nquery());
for(int t = 0; t < data.nfeature(); t++)
{
// compute the query weighted score of unchecked each weak ranker
std::vector<double> weightedScores(data.nfeature(), 0);
for(int f = 0; f < data.nfeature(); f++)
{
if(weakRankerChecked[f] == 0)
{
for(int q = 0; q < data.nquery(); q++)
{
weightedScores[f] += weakRankerScores[q][f]*queryWeights[q];
}
}
}
// find best weak ranker
int bestWR = 0;
for(int f = 0; f < data.nfeature(); f++)
{
if(weightedScores[f] > weightedScores[bestWR])
{
bestWR = f;
}
}
// compute alpha
double num = 0.0;
double den = 0.0;
for(int q = 0; q < data.nquery(); q++)
{
num += queryWeights[q]*(1.0 + weakRankerScores[q][bestWR]);
den += queryWeights[q]*(1.0 - weakRankerScores[q][bestWR]);
}
double alpha = 0.5*(log(num/den));
weakRankerWeights[bestWR] = alpha;
weakRankerChecked[bestWR] = 1;
// only update query weights if the new weak ranker improves overall performance
double newScore = metric.measure(rank(data));
if((newScore-scores.back()) > 1e-4)
{
scores.push_back(newScore);
std::vector<double> queryProbs;
for(int q = 0; q < data.nquery(); q++)
{
queryProbs.push_back(exp(-metric.measure(rank(data.getQuery(q)))));
}
double totalQueryProb = std::accumulate(queryProbs.begin(), queryProbs.end(), 0.0);
for(int q = 0; q < data.nquery(); q++)
{
queryWeights[q] = queryProbs[q]/totalQueryProb;
}
}
else
{
weakRankerWeights[bestWR] = 0.0;
}
}
}