major restructure of the training code

1 files changed, 0 insertions, 41 deletions

diff --git a/training/entropy.cc b/training/entropy.cc
deleted file mode 100644
index 4fdbe2be..00000000
--- a/training/entropy.cc
+++ /dev/null
@@ -1,41 +0,0 @@
-#include "entropy.h"
-
-#include "prob.h"
-#include "candidate_set.h"
-
-using namespace std;
-
-namespace training {
-
-// see Mann and McCallum "Efficient Computation of Entropy Gradient ..." for
-// a mostly clear derivation of:
-//   g = E[ F(x,y) * log p(y|x) ] + H(y | x) * E[ F(x,y) ]
-double CandidateSetEntropy::operator()(const vector<double>& params,
-                                       SparseVector<double>* g) const {
-  prob_t z;
-  vector<double> dps(cands_.size());
-  for (unsigned i = 0; i < cands_.size(); ++i) {
-    dps[i] = cands_[i].fmap.dot(params);
-    const prob_t u(dps[i], init_lnx());
-    z += u;
-  }
-  const double log_z = log(z);
-
-  SparseVector<double> exp_feats;
-  double entropy = 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 e_logprob = prob * log_prob;
-    entropy -= e_logprob;
-    if (g) {
-      (*g) += cands_[i].fmap * e_logprob;
-      exp_feats += cands_[i].fmap * prob;
-    }
-  }
-  if (g) (*g) += exp_feats * entropy;
-  return entropy;
-}
-
-}
-