FastForest(
this SweepableBinaryClassificationTrainers trainer,
string labelColumnName = "Label",
string featureColumnName = "Features",
SweepableOption <FastForestBinaryTrainer.Options> optionBuilder = null,
FastForestBinaryTrainer.Options defaultOption = null)
{
var context = trainer.Context;
if (optionBuilder == null)
{
optionBuilder = FastForestBinaryTrainerSweepableOptions.Default;
}
optionBuilder.SetDefaultOption(defaultOption);
return(context.AutoML().CreateSweepableEstimator(
(context, option) =>
{
option.LabelColumnName = labelColumnName;
option.FeatureColumnName = featureColumnName;
return context.BinaryClassification.Trainers.FastForest(option);
},
optionBuilder,
new string[] { labelColumnName, featureColumnName },
new string[] { PredictedLabel },
nameof(FastForestBinaryTrainer)));
}
OnlineGradientDescent(
this SweepableRegressionTrainers trainers,
string labelColumnName = "Label",
string featureColumnName = "Features",
SweepableOption <OnlineGradientDescentTrainer.Options> optionSweeper = null,
OnlineGradientDescentTrainer.Options defaultOption = null)
{
var context = trainers.Context;
if (optionSweeper == null)
{
optionSweeper = OnlineGradientDescentTrainerSweepableOptions.Default;
}
optionSweeper.SetDefaultOption(defaultOption);
return(context.AutoML().CreateSweepableEstimator(
(context, option) =>
{
option.LabelColumnName = labelColumnName;
option.FeatureColumnName = featureColumnName;
return context.Regression.Trainers.OnlineGradientDescent(option);
},
optionSweeper,
new string[] { labelColumnName, featureColumnName },
new string[] { Score },
nameof(OnlineGradientDescentTrainer)));
}
SdcaNonCalibreated(this SweepableMultiClassificationTrainers trainer, string labelColumnName = "Label", string featureColumnName = "Features", SweepableOption <SdcaNonCalibratedMulticlassTrainer.Options> optionBuilder = null, SdcaNonCalibratedMulticlassTrainer.Options defaultOption = null)
{
var context = trainer.Context;
if (optionBuilder == null)
{
optionBuilder = SdcaNonCalibratedMulticlassTrainerSweepableOptions.Default;
}
optionBuilder.SetDefaultOption(defaultOption);
return(context.AutoML().CreateSweepableEstimator(
(context, option) =>
{
option.LabelColumnName = labelColumnName;
option.FeatureColumnName = featureColumnName;
return context.MulticlassClassification.Trainers.SdcaNonCalibrated(option);
},
optionBuilder,
trainerName: nameof(SdcaNonCalibratedMulticlassTrainer),
inputs: new string[] { featureColumnName },
outputs: new string[] { PredictedLabel }));
}
LightGbm(this SweepableMultiClassificationTrainers trainer, string labelColumnName = "Label", string featureColumnName = "Features", SweepableOption <LightGbmMulticlassTrainer.Options> optionBuilder = null, LightGbmMulticlassTrainer.Options defaultOption = null)
{
var context = trainer.Context;
if (optionBuilder == null)
{
optionBuilder = LightGbmMulticlassTrainerSweepableOptions.Default;
}
optionBuilder.SetDefaultOption(defaultOption);
return(context.AutoML().CreateSweepableEstimator(
(context, option) =>
{
if (defaultOption != null)
{
Util.CopyFieldsTo(defaultOption, option);
}
option.LabelColumnName = labelColumnName;
option.FeatureColumnName = featureColumnName;
return context.MulticlassClassification.Trainers.LightGbm(option);
},
optionBuilder,
trainerName: nameof(LightGbmMulticlassTrainer),
inputs: new string[] { featureColumnName },
outputs: new string[] { PredictedLabel }));
}
public static SweepableEstimator <TNewTrain, TOption> CreateSweepableEstimator <TNewTrain, TOption>(Func <TOption, TNewTrain> estimatorFactory, SweepableOption <TOption> optionBuilder, TransformerScope scope = TransformerScope.Everything, string estimatorName = null, string[] inputs = null, string[] outputs = null)
where TNewTrain : IEstimator <ITransformer>
where TOption : class
{
return(new SweepableEstimator <TNewTrain, TOption>(estimatorFactory, optionBuilder, scope, estimatorName, inputs, outputs));
}
