1 write to Rand
Microsoft.ML.FastTree (1)
Training\TreeLearners\LeastSquaresRegressionTreeLearner.cs (1)
171Rand = new Random(randomSeed);
4 references to Rand
Microsoft.ML.FastTree (4)
Training\TreeLearners\FastForestLeastSquaresTreeLearner.cs (2)
39targets, weights, _quantileSampleCount, Rand, tree.NumLeaves, out distributionWeights), distributionWeights); 60if (infos[i].Gain > max && Rand.NextDouble() < SplitFraction || Double.IsNegativeInfinity(max))
Training\TreeLearners\LeastSquaresRegressionTreeLearner.cs (2)
457.ArgMaxRand(Rand, SplitFraction); 486bestFeature = leafSplitCandidates.FeatureSplitInfo.Select(info => info.Gain / SoftmaxTemperature).SoftArgMax(Rand);