integrated basic matrix factorization

Merge branch 'master' of git://github.com/JohnLangford/vowpal_wabbit

Conflicts:

	Makefile
	parse_regressor.cc
	sparse_dense.cc
	vw.cc

1 files changed, 32 insertions, 0 deletions

diff --git a/sparse_dense.cc b/sparse_dense.cc
index 91f6e493..f99c5a09 100644
--- a/sparse_dense.cc
+++ b/sparse_dense.cc
@@ -16,6 +16,18 @@ float sd_add(weight* weights, size_t mask, feature* begin, feature* end)
   return ret;
 }
 
+float sd_truncadd(weight* weights, size_t mask, feature* begin, feature* end, float gravity)
+{
+  float ret = 0.;
+  for (feature* f = begin; f!= end; f++)
+    {
+      float w = weights[f->weight_index & mask];
+      float wprime = real_weight(w,gravity);
+      ret += wprime*f->x;
+    }
+  return ret;
+}
+
 float sd_offset_add(weight* weights, size_t mask, feature* begin, feature* end, size_t offset)
 {
   float ret = 0.;
@@ -24,6 +36,18 @@ float sd_offset_add(weight* weights, size_t mask, feature* begin, feature* end,
   return ret;
 }
 
+float sd_offset_truncadd(weight* weights, size_t mask, feature* begin, feature* end, size_t offset, float gravity)
+{
+  float ret = 0.;
+  for (feature* f = begin; f!= end; f++)
+    {
+      float w = weights[(f->weight_index+offset) & mask];
+      float wprime = real_weight(w,gravity);
+      ret += wprime*f->x;
+    }
+  return ret;
+}
+
 void sd_offset_update(weight* weights, size_t mask, feature* begin, feature* end, size_t offset, float update, float regularization)
 {
   for (feature* f = begin; f!= end; f++) 
@@ -64,6 +88,14 @@ float one_pf_quad_predict(weight* weights, feature& f, v_array<feature> &cross_f
     sd_offset_add(weights, mask, cross_features.begin, cross_features.end, halfhash);
 }
 
+float one_pf_quad_predict_trunc(weight* weights, feature& f, v_array<feature> &cross_features, size_t mask, float gravity)
+{
+  size_t halfhash = quadratic_constant * f.weight_index;
+  
+  return f.x * 
+    sd_offset_truncadd(weights, mask, cross_features.begin, cross_features.end, halfhash, gravity);
+}
+
 float offset_quad_predict(weight* weights, feature& page_feature, v_array<feature> &offer_features, size_t mask, size_t offset)
 {
   float prediction = 0.0;