1 write to _documents
Microsoft.ML.FastTree (1)
Training\DocumentPartitioning.cs (1)
39_documents = new int[numDocuments];
27 references to _documents
Microsoft.ML.FastTree (27)
Training\DocumentPartitioning.cs (27)
110Contracts.Assert(_documents.Length == _leafBegin[tree.NumLeaves - 1] + _leafCount[tree.NumLeaves - 1]); 123_documents[documentPos++] = d; 138get { return _documents.Length; } 143get { return _documents; } 153_leafCount[0] = _documents.Length; 156for (int d = 0; d < _documents.Length; ++d) 157_documents[d] = d; 161for (int d = 0; d < _documents.Length; ++d) 162_documents[d] = _initialDocuments[d]; 184distributionWeights[count] = weights[_documents[randInst]]; 186dist[count++] = targets[_documents[randInst]]; 206_tempDocuments = new int[_documents.Length]; 214fixed (int* pDocuments = _documents) 229Array.Copy(_tempDocuments, begin, _documents, newEnd, gtCount); 252_tempDocuments = new int[_documents.Length]; 260fixed (int* pDocuments = _documents) 277Array.Copy(_tempDocuments, begin, _documents, newEnd, gtCount); 315fixed (int* pDocuments = _documents) 346yield return _documents[index]; 353Array.Copy(_documents, _leafBegin[leaf], documents, 0, _leafCount[leaf]); 359documents = _documents; 388value = array[_documents[i]]; 399mean += array[_documents[i]]; 426value = array[_documents[i]]; 429FloatType weight = (FloatType)sampleWeights[_documents[i]]; 439FloatType weight = (FloatType)sampleWeights[_documents[i]]; 440mean += array[_documents[i]] * weight;