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authorPatrick Simianer <simianer@cl.uni-heidelberg.de>2012-06-26 14:47:46 +0200
committerPatrick Simianer <simianer@cl.uni-heidelberg.de>2012-06-26 14:47:46 +0200
commit3c03e716a8638163a820dbecf652c772e6d651f2 (patch)
tree255e2aa075b9a4c2a2fb1c077e899afdc5654c19 /training/risk.cc
parentd04c516536db996e5fe5b94b8e5dea4ce2e04b4a (diff)
parente1b85b4f02045c62400b9c755883e7fae14557f6 (diff)
Merge remote-tracking branch 'upstream/master'
Diffstat (limited to 'training/risk.cc')
-rw-r--r--training/risk.cc45
1 files changed, 45 insertions, 0 deletions
diff --git a/training/risk.cc b/training/risk.cc
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+#include "risk.h"
+
+#include "prob.h"
+#include "candidate_set.h"
+#include "ns.h"
+
+using namespace std;
+
+namespace training {
+
+// g = \sum_e p(e|f) * loss(e) * (phi(e,f) - E[phi(e,f)])
+double CandidateSetRisk::operator()(const vector<double>& params,
+ SparseVector<double>* g) const {
+ prob_t z;
+ for (unsigned i = 0; i < cands_.size(); ++i) {
+ const prob_t u(cands_[i].fmap.dot(params), init_lnx());
+ z += u;
+ }
+ const double log_z = log(z);
+
+ SparseVector<double> exp_feats;
+ if (g) {
+ for (unsigned i = 0; i < cands_.size(); ++i) {
+ const double log_prob = cands_[i].fmap.dot(params) - log_z;
+ const double prob = exp(log_prob);
+ exp_feats += cands_[i].fmap * prob;
+ }
+ }
+
+ double risk = 0;
+ for (unsigned i = 0; i < cands_.size(); ++i) {
+ const double log_prob = cands_[i].fmap.dot(params) - log_z;
+ const double prob = exp(log_prob);
+ const double cost = metric_.IsErrorMetric() ? metric_.ComputeScore(cands_[i].eval_feats)
+ : 1.0 - metric_.ComputeScore(cands_[i].eval_feats);
+ const double r = prob * cost;
+ risk += r;
+ if (g) (*g) += (cands_[i].fmap - exp_feats) * r;
+ }
+ return risk;
+}
+
+}
+
+