LightGbmRegressionTrainer.Options Class
Definition
Important
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Options for the LightGbmRegressionTrainer as used in LightGbm(Options).
public sealed class LightGbmRegressionTrainer.Options : Microsoft.ML.Trainers.LightGbm.LightGbmTrainerBase<Microsoft.ML.Trainers.LightGbm.LightGbmRegressionTrainer.Options,float,Microsoft.ML.Data.RegressionPredictionTransformer<Microsoft.ML.Trainers.LightGbm.LightGbmRegressionModelParameters>,Microsoft.ML.Trainers.LightGbm.LightGbmRegressionModelParameters>.OptionsBase
type LightGbmRegressionTrainer.Options = class
inherit LightGbmTrainerBase<LightGbmRegressionTrainer.Options, single, RegressionPredictionTransformer<LightGbmRegressionModelParameters>, LightGbmRegressionModelParameters>.OptionsBase
Public NotInheritable Class LightGbmRegressionTrainer.Options
Inherits LightGbmTrainerBase(Of LightGbmRegressionTrainer.Options, Single, RegressionPredictionTransformer(Of LightGbmRegressionModelParameters), LightGbmRegressionModelParameters).OptionsBase
- Inheritance
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LightGbmTrainerBase<LightGbmRegressionTrainer.Options,Single,RegressionPredictionTransformer<LightGbmRegressionModelParameters>,LightGbmRegressionModelParameters>.OptionsBaseLightGbmRegressionTrainer.Options
Constructors
LightGbmRegressionTrainer.Options() |
Fields
BatchSize |
Number of data points per batch, when loading data. (Inherited from LightGbmTrainerBase<TOptions,TOutput,TTransformer,TModel>.OptionsBase) |
CategoricalSmoothing |
Laplace smooth term in categorical feature split. This can reduce the effect of noises in categorical features, especially for categories with few data. (Inherited from LightGbmTrainerBase<TOptions,TOutput,TTransformer,TModel>.OptionsBase) |
EarlyStoppingRound |
Determines the number of rounds, after which training will stop if validation metric doesn't improve. (Inherited from LightGbmTrainerBase<TOptions,TOutput,TTransformer,TModel>.OptionsBase) |
EvaluationMetric |
Determines what evaluation metric to use. |
ExampleWeightColumnName |
Column to use for example weight. (Inherited from TrainerInputBaseWithWeight) |
FeatureColumnName |
Column to use for features. (Inherited from TrainerInputBase) |
HandleMissingValue |
Whether to enable special handling of missing value or not. (Inherited from LightGbmTrainerBase<TOptions,TOutput,TTransformer,TModel>.OptionsBase) |
L2CategoricalRegularization |
L2 regularization for categorical split. (Inherited from LightGbmTrainerBase<TOptions,TOutput,TTransformer,TModel>.OptionsBase) |
LabelColumnName |
Column to use for labels. (Inherited from TrainerInputBaseWithLabel) |
LearningRate |
The shrinkage rate for trees, used to prevent over-fitting. (Inherited from LightGbmTrainerBase<TOptions,TOutput,TTransformer,TModel>.OptionsBase) |
MaximumBinCountPerFeature |
The maximum number of bins that feature values will be bucketed in. (Inherited from LightGbmTrainerBase<TOptions,TOutput,TTransformer,TModel>.OptionsBase) |
MaximumCategoricalSplitPointCount |
Maximum categorical split points to consider when splitting on a categorical feature. (Inherited from LightGbmTrainerBase<TOptions,TOutput,TTransformer,TModel>.OptionsBase) |
MinimumExampleCountPerGroup |
The minimum number of data points per categorical group. (Inherited from LightGbmTrainerBase<TOptions,TOutput,TTransformer,TModel>.OptionsBase) |
MinimumExampleCountPerLeaf |
The minimal number of data points required to form a new tree leaf. (Inherited from LightGbmTrainerBase<TOptions,TOutput,TTransformer,TModel>.OptionsBase) |
NumberOfIterations |
The number of boosting iterations. A new tree is created in each iteration, so this is equivalent to the number of trees. (Inherited from LightGbmTrainerBase<TOptions,TOutput,TTransformer,TModel>.OptionsBase) |
NumberOfLeaves |
The maximum number of leaves in one tree. (Inherited from LightGbmTrainerBase<TOptions,TOutput,TTransformer,TModel>.OptionsBase) |
NumberOfThreads |
Determines the number of threads used to run LightGBM. (Inherited from LightGbmTrainerBase<TOptions,TOutput,TTransformer,TModel>.OptionsBase) |
RowGroupColumnName |
Column to use for example groupId. (Inherited from TrainerInputBaseWithGroupId) |
Seed |
The random seed for LightGBM to use. (Inherited from LightGbmTrainerBase<TOptions,TOutput,TTransformer,TModel>.OptionsBase) |
Silent |
Controls the logging level in LighGBM. (Inherited from LightGbmTrainerBase<TOptions,TOutput,TTransformer,TModel>.OptionsBase) |
UseCategoricalSplit |
Whether to enable categorical split or not. (Inherited from LightGbmTrainerBase<TOptions,TOutput,TTransformer,TModel>.OptionsBase) |
UseZeroAsMissingValue |
Whether to enable the usage of zero (0) as missing value. (Inherited from LightGbmTrainerBase<TOptions,TOutput,TTransformer,TModel>.OptionsBase) |
Verbose |
Determines whether to output progress status during training and evaluation. (Inherited from LightGbmTrainerBase<TOptions,TOutput,TTransformer,TModel>.OptionsBase) |
Properties
Booster |
Booster parameter to use (Inherited from LightGbmTrainerBase<TOptions,TOutput,TTransformer,TModel>.OptionsBase) |