| 113 | }\ |
| 114 | |
| 115 | void Tree::AddPredictionToScore(const Dataset* data, data_size_t num_data, double* score) const { |
| 116 | if (num_leaves_ <= 1) { |
| 117 | if (leaf_value_[0] != 0.0f) { |
| 118 | #pragma omp parallel for schedule(static) |
| 119 | for (data_size_t i = 0; i < num_data; ++i) { |
| 120 | score[i] += leaf_value_[0]; |
| 121 | } |
| 122 | } |
| 123 | return; |
| 124 | } |
| 125 | std::vector<uint32_t> default_bins(num_leaves_ - 1); |
| 126 | std::vector<uint32_t> max_bins(num_leaves_ - 1); |
| 127 | for (int i = 0; i < num_leaves_ - 1; ++i) { |
| 128 | const int fidx = split_feature_inner_[i]; |
| 129 | auto bin_mapper = data->FeatureBinMapper(fidx); |
| 130 | default_bins[i] = bin_mapper->GetDefaultBin(); |
| 131 | max_bins[i] = bin_mapper->num_bin() - 1; |
| 132 | } |
| 133 | if (num_cat_ > 0) { |
| 134 | if (data->num_features() > num_leaves_ - 1) { |
| 135 | Threading::For<data_size_t>(0, num_data, [this, &data, score, &default_bins, &max_bins] |
| 136 | (int, data_size_t start, data_size_t end) { |
| 137 | PredictionFun(num_leaves_ - 1, split_feature_inner_[i], start, DecisionInner, node, i); |
| 138 | }); |
| 139 | } else { |
| 140 | Threading::For<data_size_t>(0, num_data, [this, &data, score, &default_bins, &max_bins] |
| 141 | (int, data_size_t start, data_size_t end) { |
| 142 | PredictionFun(data->num_features(), i, start, DecisionInner, split_feature_inner_[node], i); |
| 143 | }); |
| 144 | } |
| 145 | } else { |
| 146 | if (data->num_features() > num_leaves_ - 1) { |
| 147 | Threading::For<data_size_t>(0, num_data, [this, &data, score, &default_bins, &max_bins] |
| 148 | (int, data_size_t start, data_size_t end) { |
| 149 | PredictionFun(num_leaves_ - 1, split_feature_inner_[i], start, NumericalDecisionInner, node, i); |
| 150 | }); |
| 151 | } else { |
| 152 | Threading::For<data_size_t>(0, num_data, [this, &data, score, &default_bins, &max_bins] |
| 153 | (int, data_size_t start, data_size_t end) { |
| 154 | PredictionFun(data->num_features(), i, start, NumericalDecisionInner, split_feature_inner_[node], i); |
| 155 | }); |
| 156 | } |
| 157 | } |
| 158 | } |
| 159 | |
| 160 | void Tree::AddPredictionToScore(const Dataset* data, |
| 161 | const data_size_t* used_data_indices, |
no test coverage detected