add un_balance to multi class (#314)

* add un_balance to multi class

* change the calculation of label weights

src/objective/multiclass_objective.hpp

@@ -14,6 +14,7 @@ class MulticlassLogloss: public ObjectiveFunction {
 public:
   explicit MulticlassLogloss(const ObjectiveConfig& config) {
     num_class_ = config.num_class;
+    is_unbalance_ = config.is_unbalance;
   }
 
   ~MulticlassLogloss() {
@@ -24,12 +25,25 @@ public:
     label_ = metadata.label();
     weights_ = metadata.weights();
     label_int_.resize(num_data_);
-    for (int i = 0; i < num_data_; ++i){
-        label_int_[i] = static_cast<int>(label_[i]);
-        if (label_int_[i] < 0 || label_int_[i] >= num_class_) {
-            Log::Fatal("Label must be in [0, %d), but found %d in label", num_class_, label_int_[i]);
-        }
+    #pragma omp parallel for schedule(static)
+    for (int i = 0; i < num_data_; ++i) {
+      label_int_[i] = static_cast<int>(label_[i]);
+      if (label_int_[i] < 0 || label_int_[i] >= num_class_) {
+        Log::Fatal("Label must be in [0, %d), but found %d in label", num_class_, label_int_[i]);
+      }
     }
+    label_pos_weights_ = std::vector<float>(num_class_, 1);
+    if (is_unbalance_) {
+      std::vector<int> cnts(num_class_, 0);
+      for (int i = 0; i < num_data_; ++i) {
+        ++cnts[label_int_[i]];
+      }
+      for (int i = 0; i < num_class_; ++i) {
+        int cnt_cur = cnts[i];
+        int cnt_other = (num_data_ - cnts[i]);
+        label_pos_weights_[i] = static_cast<float>(cnt_other) / cnt_cur;
+      }
+    } 
   }
 
   void GetGradients(const double* score, score_t* gradients, score_t* hessians) const override {
@@ -46,11 +60,12 @@ public:
           auto p = rec[k];
           size_t idx = static_cast<size_t>(num_data_) * k + i;
           if (label_int_[i] == k) {
-            gradients[idx] = static_cast<score_t>(p - 1.0f);
+            gradients[idx] = static_cast<score_t>(p - 1.0f) * label_pos_weights_[k];
+            hessians[idx] = static_cast<score_t>(2.0f * p * (1.0f - p))* label_pos_weights_[k];
           } else {
             gradients[idx] = static_cast<score_t>(p);
+            hessians[idx] = static_cast<score_t>(2.0f * p * (1.0f - p));
           }
-          hessians[idx] = static_cast<score_t>(2.0f * p * (1.0f - p));
         }
       }
     } else {
@@ -66,11 +81,13 @@ public:
           auto p = rec[k];
           size_t idx = static_cast<size_t>(num_data_) * k + i;
           if (label_int_[i] == k) {
-            gradients[idx] = static_cast<score_t>((p - 1.0f) * weights_[i]);
+            gradients[idx] = static_cast<score_t>((p - 1.0f) * weights_[i]) * label_pos_weights_[k];
+            hessians[idx] = static_cast<score_t>(2.0f * p * (1.0f - p) * weights_[i]) * label_pos_weights_[k];
           } else {
             gradients[idx] = static_cast<score_t>(p * weights_[i]);
+            hessians[idx] = static_cast<score_t>(2.0f * p * (1.0f - p) * weights_[i]);
           }
-          hessians[idx] = static_cast<score_t>(2.0f * p * (1.0f - p) * weights_[i]);
+          
         }
       }
     }
@@ -91,6 +108,9 @@ private:
   std::vector<int> label_int_;
   /*! \brief Weights for data */
   const float* weights_;
+  /*! \brief Weights for label */
+  std::vector<float> label_pos_weights_;
+  bool is_unbalance_;
 };
 
 }  // namespace LightGBM