GamRegressionTrainer.Options Class
Definition
Important
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Options for the GamRegressionTrainer as used in Gam(Options).
public class GamRegressionTrainer.Options : Microsoft.ML.Trainers.FastTree.GamTrainerBase<Microsoft.ML.Trainers.FastTree.GamRegressionTrainer.Options,Microsoft.ML.Data.RegressionPredictionTransformer<Microsoft.ML.Trainers.FastTree.GamRegressionModelParameters>,Microsoft.ML.Trainers.FastTree.GamRegressionModelParameters>.OptionsBasetype GamRegressionTrainer.Options = class
inherit GamTrainerBase<GamRegressionTrainer.Options, RegressionPredictionTransformer<GamRegressionModelParameters>, GamRegressionModelParameters>.OptionsBasePublic Class GamRegressionTrainer.Options
Inherits GamTrainerBase(Of GamRegressionTrainer.Options, RegressionPredictionTransformer(Of GamRegressionModelParameters), GamRegressionModelParameters).OptionsBase- Inheritance
Constructors
| GamRegressionTrainer.Options() |
Fields
| DiskTranspose |
Whether to utilize the disk or the data's native transposition facilities (where applicable) when performing the transpose. (Inherited from GamTrainerBase<TOptions,TTransformer,TPredictor>.OptionsBase) |
| EnablePruning |
Enable post-training tree pruning to avoid overfitting. It requires a validation set. (Inherited from GamTrainerBase<TOptions,TTransformer,TPredictor>.OptionsBase) |
| EntropyCoefficient |
The entropy (regularization) coefficient between 0 and 1. (Inherited from GamTrainerBase<TOptions,TTransformer,TPredictor>.OptionsBase) |
| ExampleWeightColumnName |
Column to use for example weight. (Inherited from TrainerInputBaseWithWeight) |
| FeatureColumnName |
Column to use for features. (Inherited from TrainerInputBase) |
| FeatureFlocks |
Whether to collectivize features during dataset preparation to speed up training. (Inherited from GamTrainerBase<TOptions,TTransformer,TPredictor>.OptionsBase) |
| GainConfidenceLevel |
Tree fitting gain confidence requirement. Only consider a gain if its likelihood versus a random choice gain is above this value. (Inherited from GamTrainerBase<TOptions,TTransformer,TPredictor>.OptionsBase) |
| GetDerivativesSampleRate |
Sample each query 1 in k times in the GetDerivatives function. (Inherited from GamTrainerBase<TOptions,TTransformer,TPredictor>.OptionsBase) |
| LabelColumnName |
Column to use for labels. (Inherited from TrainerInputBaseWithLabel) |
| LearningRate |
The learning rate. (Inherited from GamTrainerBase<TOptions,TTransformer,TPredictor>.OptionsBase) |
| MaximumBinCountPerFeature |
The maximum number of distinct values (bins) per feature. (Inherited from GamTrainerBase<TOptions,TTransformer,TPredictor>.OptionsBase) |
| MaximumTreeOutput |
The upper bound on the absolute value of a single tree output. (Inherited from GamTrainerBase<TOptions,TTransformer,TPredictor>.OptionsBase) |
| MinimumExampleCountPerLeaf |
The minimal number of data points required to form a new tree leaf. (Inherited from GamTrainerBase<TOptions,TTransformer,TPredictor>.OptionsBase) |
| NumberOfIterations |
Total number of passes over the training data. (Inherited from GamTrainerBase<TOptions,TTransformer,TPredictor>.OptionsBase) |
| NumberOfThreads |
The number of threads to use. (Inherited from GamTrainerBase<TOptions,TTransformer,TPredictor>.OptionsBase) |
| PruningMetrics |
Determines what metric to use for pruning. |
| Seed |
The seed of the random number generator. (Inherited from GamTrainerBase<TOptions,TTransformer,TPredictor>.OptionsBase) |