fix all negative values in cat features (#1547)

* fix all negative values in cat features

* fix a bug

src/io/bin.cpp

@@ -316,55 +316,58 @@ namespace LightGBM {
           }
         }
       }
-      // sort by counts
-      Common::SortForPair<int, int>(counts_int, distinct_values_int, 0, true);
-      // avoid first bin is zero
-      if (distinct_values_int[0] == 0) {
-        if (counts_int.size() == 1) {
-          counts_int.push_back(0);
-          distinct_values_int.push_back(distinct_values_int[0] + 1);
-        }
-        std::swap(counts_int[0], counts_int[1]);
-        std::swap(distinct_values_int[0], distinct_values_int[1]);
-      }
-      // will ignore the categorical of small counts
-      int cut_cnt = static_cast<int>((total_sample_cnt - na_cnt) * 0.99f);
-      size_t cur_cat = 0;
-      categorical_2_bin_.clear();
-      bin_2_categorical_.clear();
       num_bin_ = 0;
-      int used_cnt = 0;
-      max_bin = std::min(static_cast<int>(distinct_values_int.size()), max_bin);
-      cnt_in_bin.clear();
-      while (cur_cat < distinct_values_int.size()
-        && (used_cnt < cut_cnt || num_bin_ < max_bin)) {
-        if (counts_int[cur_cat] < min_data_in_bin && cur_cat > 1) {
-          break;
+      int rest_cnt = total_sample_cnt - na_cnt;
+      if (rest_cnt > 0) {
+        // sort by counts
+        Common::SortForPair<int, int>(counts_int, distinct_values_int, 0, true);
+        // avoid first bin is zero
+        if (distinct_values_int[0] == 0) {
+          if (counts_int.size() == 1) {
+            counts_int.push_back(0);
+            distinct_values_int.push_back(distinct_values_int[0] + 1);
+          }
+          std::swap(counts_int[0], counts_int[1]);
+          std::swap(distinct_values_int[0], distinct_values_int[1]);
         }
-        bin_2_categorical_.push_back(distinct_values_int[cur_cat]);
-        categorical_2_bin_[distinct_values_int[cur_cat]] = static_cast<unsigned int>(num_bin_);
-        used_cnt += counts_int[cur_cat];
-        cnt_in_bin.push_back(counts_int[cur_cat]);
-        ++num_bin_;
-        ++cur_cat;
-      }
-      // need an additional bin for NaN
-      if (cur_cat == distinct_values_int.size() && na_cnt > 0) {
-        // use -1 to represent NaN
-        bin_2_categorical_.push_back(-1);
-        categorical_2_bin_[-1] = num_bin_;
-        cnt_in_bin.push_back(0);
-        ++num_bin_;
-      }
-      // Use MissingType::None to represent this bin contains all categoricals
-      if (cur_cat == distinct_values_int.size() && na_cnt == 0) {
-        missing_type_ = MissingType::None;
-      } else if (na_cnt == 0) {
-        missing_type_ = MissingType::Zero;
-      } else {
-        missing_type_ = MissingType::NaN;
+        // will ignore the categorical of small counts
+        int cut_cnt = static_cast<int>((total_sample_cnt - na_cnt) * 0.99f);
+        size_t cur_cat = 0;
+        categorical_2_bin_.clear();
+        bin_2_categorical_.clear();
+        int used_cnt = 0;
+        max_bin = std::min(static_cast<int>(distinct_values_int.size()), max_bin);
+        cnt_in_bin.clear();
+        while (cur_cat < distinct_values_int.size()
+               && (used_cnt < cut_cnt || num_bin_ < max_bin)) {
+          if (counts_int[cur_cat] < min_data_in_bin && cur_cat > 1) {
+            break;
+          }
+          bin_2_categorical_.push_back(distinct_values_int[cur_cat]);
+          categorical_2_bin_[distinct_values_int[cur_cat]] = static_cast<unsigned int>(num_bin_);
+          used_cnt += counts_int[cur_cat];
+          cnt_in_bin.push_back(counts_int[cur_cat]);
+          ++num_bin_;
+          ++cur_cat;
+        }
+        // need an additional bin for NaN
+        if (cur_cat == distinct_values_int.size() && na_cnt > 0) {
+          // use -1 to represent NaN
+          bin_2_categorical_.push_back(-1);
+          categorical_2_bin_[-1] = num_bin_;
+          cnt_in_bin.push_back(0);
+          ++num_bin_;
+        }
+        // Use MissingType::None to represent this bin contains all categoricals
+        if (cur_cat == distinct_values_int.size() && na_cnt == 0) {
+          missing_type_ = MissingType::None;
+        } else if (na_cnt == 0) {
+          missing_type_ = MissingType::Zero;
+        } else {
+          missing_type_ = MissingType::NaN;
+        }
+        cnt_in_bin.back() += static_cast<int>(total_sample_cnt - used_cnt);
       }
-      cnt_in_bin.back() += static_cast<int>(total_sample_cnt - used_cnt);
     }
 
     // check trival(num_bin_ == 1) feature
@@ -384,8 +387,12 @@ namespace LightGBM {
         CHECK(default_bin_ > 0);
       }
     }
-    // calculate sparse rate
-    sparse_rate_ = static_cast<double>(cnt_in_bin[default_bin_]) / static_cast<double>(total_sample_cnt);
+    if (!is_trival_) {
+      // calculate sparse rate
+      sparse_rate_ = static_cast<double>(cnt_in_bin[default_bin_]) / static_cast<double>(total_sample_cnt);
+    } else {
+      sparse_rate_ = 1.0f;
+    }
   }