2 writes to _trees
Microsoft.ML.FastTree (2)
TreeEnsemble\InternalTreeEnsemble.cs (2)
36_trees = new List<InternalRegressionTree>(); 50_trees = new List<InternalRegressionTree>();
27 references to _trees
Microsoft.ML.FastTree (27)
TreeEnsemble\InternalTreeEnsemble.cs (27)
28public IEnumerable<InternalRegressionTree> Trees => _trees; 32public int NumTrees => _trees.Count; 75public void AddTree(InternalRegressionTree tree) => _trees.Add(tree); 76public void AddTreeAt(InternalRegressionTree tree, int index) => _trees.Insert(index, tree); 77public void RemoveTree(int index) => _trees.RemoveAt(index); 79public void RemoveAfter(int index) => _trees.RemoveRange(index, NumTrees - index); 80public InternalRegressionTree GetTreeAt(int index) => _trees[index]; 132_trees[w].ToTreeEnsembleFormat(sbEvaluator, sbInput, fmap, ref evaluatorCounter, featureToID); 171sb.AppendFormat("{0}", _trees[0].Weight); 180sb.Append(_trees[w].Weight); 236double[] values = new double[_trees.Count]; 237for (int w = 0; w < _trees.Count; ++w) 238values[w] = _trees[w].MaxOutput; 246output += _trees[h].GetOutput(featureBins); 254output += _trees[h].GetOutput(binnedInstance); 262output += _trees[h].GetOutput(in feat); 270if (((InternalQuantileRegressionTree)_trees[0]).IsWeightedTargets) 277((InternalQuantileRegressionTree)_trees[h]).LoadSampledLabels(in feat, distribution, 285return GetOutput(featureBins, _trees.Count); 290if (prefix > _trees.Count || prefix < 0) 291prefix = _trees.Count; 313if (_trees.Count == 0) 319if (prefix > _trees.Count || prefix < 0) 320prefix = _trees.Count; 321FeatureToGainMap gainMap = new FeatureToGainMap(_trees.Take(prefix).ToList(), normalize); 356foreach (var tree in _trees) 370var tree = _trees[i];