1 write to BinEffects
Microsoft.ML.FastTree (1)
GamTrainer.cs (1)
445BinEffects = new double[TrainSet.NumFeatures][];
18 references to BinEffects
Microsoft.ML.FastTree (18)
GamClassification.cs (1)
141BinUpperBounds, BinEffects, MeanEffect, InputLength, FeatureMap);
GamRegression.cs (1)
109return new GamRegressionModelParameters(Host, BinUpperBounds, BinEffects, MeanEffect, InputLength, FeatureMap);
GamTrainer.cs (16)
450BinEffects[featureIndex] = new double[numOfBins]; 456BinEffects[featureIndex][bin] += _subGraph.Splits[featureIndex][iteration].LteValue; 458BinEffects[featureIndex][bin] += _subGraph.Splits[featureIndex][iteration].GtValue; 497var meanEffects = new double[BinEffects.Length]; 503for (int featureIndex = 0; featureIndex < BinEffects.Length; featureIndex++) 514newTotalEffect = totalEffect + BinEffects[featureIndex][bin]; 526for (int featureIndex = 0; featureIndex < BinEffects.Length; featureIndex++) 533for (int bin = 0; bin < BinEffects[featureIndex].Length; ++bin) 534BinEffects[featureIndex][bin] -= meanEffects[featureIndex]; 552double value = BinEffects[i][0]; 553for (int j = 0; j < BinEffects[i].Length; j++) 555double element = BinEffects[i][j]; 564newBinBoundaries.Add(binUpperBound[BinEffects[i].Length - 1]); 565newBinEffects.Add(BinEffects[i][BinEffects[i].Length - 1]); 569BinEffects[i] = newBinEffects.ToArray();