convert the probabilities to raw score in boost_from_average of classification.

include/LightGBM/objective_function.h

@@ -33,6 +33,10 @@ public:
 
   virtual const char* GetName() const = 0;
 
+  virtual std::vector<double> ConvertToRawScore(const std::vector<double>& preds) const {
+    return preds;
+  }
+
   ObjectiveFunction() = default;
   /*! \brief Disable copy */
   ObjectiveFunction& operator=(const ObjectiveFunction&) = delete;

src/boosting/gbdt.cpp

@@ -306,13 +306,17 @@ bool GBDT::TrainOneIter(const score_t* gradient, const score_t* hessian, bool is
         sum_per_class[0] += label[i];
       }
     }
+    std::vector<double > init_scores(num_class_);
+    for (int i = 0; i < num_class_; ++i) {
+      init_scores[i] = sum_per_class[i] / num_data_;
+    }
+    init_scores = object_function_->ConvertToRawScore(init_scores);
     for (int curr_class = 0; curr_class < num_class_; ++curr_class) {
-      double init_score = sum_per_class[curr_class] / num_data_;
       std::unique_ptr<Tree> new_tree(new Tree(2));
-      new_tree->Split(0, 0, BinType::NumericalBin, 0, 0, 0, init_score, init_score, 0, num_data_, 1);
-      train_score_updater_->AddScore(init_score, curr_class);
+      new_tree->Split(0, 0, BinType::NumericalBin, 0, 0, 0, init_scores[curr_class], init_scores[curr_class], 0, num_data_, 1);
+      train_score_updater_->AddScore(init_scores[curr_class], curr_class);
       for (auto& score_updater : valid_score_updater_) {
-        score_updater->AddScore(init_score, curr_class);
+        score_updater->AddScore(init_scores[curr_class], curr_class);
       }
       models_.push_back(std::move(new_tree));
     }

src/objective/binary_objective.hpp

@@ -86,6 +86,18 @@ public:
     }
   }
 
+  std::vector<double> ConvertToRawScore(const std::vector<double>& preds) const override {
+    std::vector<double> ret;
+    for (auto pred : preds) {
+      if (pred > kEpsilon && pred < 1.0f) {
+        ret.push_back(-std::log(1.0f / pred - 1.0f) / sigmoid_);
+      } else {
+        ret.push_back(0.0f);
+      }
+    }
+    return ret;
+  }
+
   const char* GetName() const override {
     return "binary";
   }

src/objective/multiclass_objective.hpp

@@ -93,6 +93,18 @@ public:
     }
   }
 
+  std::vector<double> ConvertToRawScore(const std::vector<double>& preds) const override {
+    std::vector<double> ret;
+    for (auto pred : preds) {
+      if (pred > kEpsilon) {
+        ret.push_back(std::log(pred));
+      } else {
+        ret.push_back(0);
+      }
+    }
+    return ret;
+  }
+
   const char* GetName() const override {
     return "multiclass";
   }