fix base score, and print message

src/tree/updater_prune-inl.hpp

@@ -19,6 +19,7 @@ class TreePruner: public IUpdater<FMatrix> {
   // set training parameter
   virtual void SetParam(const char *name, const char *val) {
     param.SetParam(name, val);
+    if (!strcmp(name, "silent")) silent = atoi(val);
   }
   // update the tree, do pruning
   virtual void Update(const std::vector<bst_gpair> &gpair,
@@ -32,33 +33,41 @@ class TreePruner: public IUpdater<FMatrix> {
 
  private:
   // try to prune off current leaf
-  inline void TryPruneLeaf(RegTree &tree, int nid, int depth) {
-    if (tree[nid].is_root()) return;
+  inline int TryPruneLeaf(RegTree &tree, int nid, int depth, int npruned) {
+    if (tree[nid].is_root()) return npruned;
     int pid = tree[nid].parent();
     RegTree::NodeStat &s = tree.stat(pid);
     ++s.leaf_child_cnt;
-
     if (s.leaf_child_cnt >= 2 && param.need_prune(s.loss_chg, depth - 1)) {
       // need to be pruned
       tree.ChangeToLeaf(pid, param.learning_rate * s.base_weight);
       // tail recursion
-      this->TryPruneLeaf(tree, pid, depth - 1);
-    }
+      return this->TryPruneLeaf(tree, pid, depth - 1, npruned+2);
+    } else {
+      return npruned;
+    }    
   }
   /*! \brief do prunning of a tree */
   inline void DoPrune(RegTree &tree) {
+    int npruned = 0;
     // initialize auxiliary statistics
     for (int nid = 0; nid < tree.param.num_nodes; ++nid) {
       tree.stat(nid).leaf_child_cnt = 0;
     }
     for (int nid = 0; nid < tree.param.num_nodes; ++nid) {
       if (tree[nid].is_leaf()) {
-        this->TryPruneLeaf(tree, nid, tree.GetDepth(nid));
+        npruned = this->TryPruneLeaf(tree, nid, tree.GetDepth(nid), npruned);
       }
     }
+    if (silent == 0) {
+      printf("tree prunning end, %d roots, %d extra nodes, %d pruned nodes ,max_depth=%d\n",
+             tree.param.num_roots, tree.num_extra_nodes(), npruned, tree.MaxDepth());
+    }
   }
 
  private:
+  // shutup
+  int silent;
   // training parameter
   TrainParam param;
 };