ExperimentBase<TMetrics,TExperimentSettings>.Execute ExperimentBase<TMetrics,TExperimentSettings>.Execute ExperimentBase<TMetrics,TExperimentSettings>.Execute Method

Definition

Overloads

Execute(IDataView, ColumnInformation, IEstimator<ITransformer>, IProgress<RunDetail<TMetrics>>) Execute(IDataView, ColumnInformation, IEstimator<ITransformer>, IProgress<RunDetail<TMetrics>>)

Executes an AutoML experiment.

Execute(IDataView, IDataView, ColumnInformation, IEstimator<ITransformer>, IProgress<RunDetail<TMetrics>>) Execute(IDataView, IDataView, ColumnInformation, IEstimator<ITransformer>, IProgress<RunDetail<TMetrics>>)

Executes an AutoML experiment.

Execute(IDataView, IDataView, String, IEstimator<ITransformer>, IProgress<RunDetail<TMetrics>>) Execute(IDataView, IDataView, String, IEstimator<ITransformer>, IProgress<RunDetail<TMetrics>>) Execute(IDataView, IDataView, String, IEstimator<ITransformer>, IProgress<RunDetail<TMetrics>>)

Executes an AutoML experiment.

Execute(IDataView, String, String, IEstimator<ITransformer>, IProgress<RunDetail<TMetrics>>) Execute(IDataView, String, String, IEstimator<ITransformer>, IProgress<RunDetail<TMetrics>>) Execute(IDataView, String, String, IEstimator<ITransformer>, IProgress<RunDetail<TMetrics>>)

Executes an AutoML experiment.

Execute(IDataView, UInt32, ColumnInformation, IEstimator<ITransformer>, IProgress<CrossValidationRunDetail<TMetrics>>) Execute(IDataView, UInt32, ColumnInformation, IEstimator<ITransformer>, IProgress<CrossValidationRunDetail<TMetrics>>)

Executes an AutoML experiment.

Execute(IDataView, UInt32, String, String, IEstimator<ITransformer>, Progress<CrossValidationRunDetail<TMetrics>>) Execute(IDataView, UInt32, String, String, IEstimator<ITransformer>, Progress<CrossValidationRunDetail<TMetrics>>) Execute(IDataView, UInt32, String, String, IEstimator<ITransformer>, Progress<CrossValidationRunDetail<TMetrics>>)

Executes an AutoML experiment.

Execute(IDataView, ColumnInformation, IEstimator<ITransformer>, IProgress<RunDetail<TMetrics>>) Execute(IDataView, ColumnInformation, IEstimator<ITransformer>, IProgress<RunDetail<TMetrics>>)

Executes an AutoML experiment.

public Microsoft.ML.AutoML.ExperimentResult<TMetrics> Execute (Microsoft.ML.IDataView trainData, Microsoft.ML.AutoML.ColumnInformation columnInformation, Microsoft.ML.IEstimator<Microsoft.ML.ITransformer> preFeaturizer = null, IProgress<Microsoft.ML.AutoML.RunDetail<TMetrics>> progressHandler = null);
member this.Execute : Microsoft.ML.IDataView * Microsoft.ML.AutoML.ColumnInformation * Microsoft.ML.IEstimator<Microsoft.ML.ITransformer> * IProgress<Microsoft.ML.AutoML.RunDetail<'Metrics>> -> Microsoft.ML.AutoML.ExperimentResult<'Metrics (requires 'Metrics : null)>

Parameters

trainData
IDataView IDataView IDataView

The training data to be used by the AutoML experiment.

columnInformation
ColumnInformation ColumnInformation ColumnInformation

Column information for the dataset.

preFeaturizer
IEstimator<ITransformer>

Pre-featurizer that AutoML will apply to the data during an experiment. (The pre-featurizer will be fit only on the training data split to produce a trained transform. Then, the trained transform will be applied to both the training data split and corresponding validation data split.)

progressHandler
IProgress<RunDetail<TMetrics>>

A user-defined object that implements the IProgress<T> interface. AutoML will invoke the method Report(T) after each model it produces during the course of the experiment.

Returns

Remarks

Depending on the size of your data, the AutoML experiment could take a long time to execute.

Execute(IDataView, IDataView, ColumnInformation, IEstimator<ITransformer>, IProgress<RunDetail<TMetrics>>) Execute(IDataView, IDataView, ColumnInformation, IEstimator<ITransformer>, IProgress<RunDetail<TMetrics>>)

Executes an AutoML experiment.

public Microsoft.ML.AutoML.ExperimentResult<TMetrics> Execute (Microsoft.ML.IDataView trainData, Microsoft.ML.IDataView validationData, Microsoft.ML.AutoML.ColumnInformation columnInformation, Microsoft.ML.IEstimator<Microsoft.ML.ITransformer> preFeaturizer = null, IProgress<Microsoft.ML.AutoML.RunDetail<TMetrics>> progressHandler = null);
member this.Execute : Microsoft.ML.IDataView * Microsoft.ML.IDataView * Microsoft.ML.AutoML.ColumnInformation * Microsoft.ML.IEstimator<Microsoft.ML.ITransformer> * IProgress<Microsoft.ML.AutoML.RunDetail<'Metrics>> -> Microsoft.ML.AutoML.ExperimentResult<'Metrics (requires 'Metrics : null)>

Parameters

trainData
IDataView IDataView IDataView

The training data to be used by the AutoML experiment.

validationData
IDataView IDataView IDataView

The validation data to be used by the AutoML experiment.

columnInformation
ColumnInformation ColumnInformation ColumnInformation

Column information for the dataset.

preFeaturizer
IEstimator<ITransformer>

Pre-featurizer that AutoML will apply to the data during an experiment. (The pre-featurizer will be fit only on the training data split to produce a trained transform. Then, the trained transform will be applied to both the training data split and corresponding validation data split.)

progressHandler
IProgress<RunDetail<TMetrics>>

A user-defined object that implements the IProgress<T> interface. AutoML will invoke the method Report(T) after each model it produces during the course of the experiment.

Returns

Remarks

Depending on the size of your data, the AutoML experiment could take a long time to execute.

Execute(IDataView, IDataView, String, IEstimator<ITransformer>, IProgress<RunDetail<TMetrics>>) Execute(IDataView, IDataView, String, IEstimator<ITransformer>, IProgress<RunDetail<TMetrics>>) Execute(IDataView, IDataView, String, IEstimator<ITransformer>, IProgress<RunDetail<TMetrics>>)

Executes an AutoML experiment.

public Microsoft.ML.AutoML.ExperimentResult<TMetrics> Execute (Microsoft.ML.IDataView trainData, Microsoft.ML.IDataView validationData, string labelColumnName = "Label", Microsoft.ML.IEstimator<Microsoft.ML.ITransformer> preFeaturizer = null, IProgress<Microsoft.ML.AutoML.RunDetail<TMetrics>> progressHandler = null);
member this.Execute : Microsoft.ML.IDataView * Microsoft.ML.IDataView * string * Microsoft.ML.IEstimator<Microsoft.ML.ITransformer> * IProgress<Microsoft.ML.AutoML.RunDetail<'Metrics>> -> Microsoft.ML.AutoML.ExperimentResult<'Metrics (requires 'Metrics : null)>
Public Function Execute (trainData As IDataView, validationData As IDataView, Optional labelColumnName As String = "Label", Optional preFeaturizer As IEstimator(Of ITransformer) = null, Optional progressHandler As IProgress(Of RunDetail(Of TMetrics)) = null) As ExperimentResult(Of TMetrics)

Parameters

trainData
IDataView IDataView IDataView

The training data to be used by the AutoML experiment.

validationData
IDataView IDataView IDataView

The validation data to be used by the AutoML experiment.

labelColumnName
String String String

The name of the label column.

preFeaturizer
IEstimator<ITransformer>

Pre-featurizer that AutoML will apply to the data during an experiment. (The pre-featurizer will be fit only on the training data split to produce a trained transform. Then, the trained transform will be applied to both the training data split and corresponding validation data split.)

progressHandler
IProgress<RunDetail<TMetrics>>

A user-defined object that implements the IProgress<T> interface. AutoML will invoke the method Report(T) after each model it produces during the course of the experiment.

Returns

Remarks

Depending on the size of your data, the AutoML experiment could take a long time to execute.

Execute(IDataView, String, String, IEstimator<ITransformer>, IProgress<RunDetail<TMetrics>>) Execute(IDataView, String, String, IEstimator<ITransformer>, IProgress<RunDetail<TMetrics>>) Execute(IDataView, String, String, IEstimator<ITransformer>, IProgress<RunDetail<TMetrics>>)

Executes an AutoML experiment.

public Microsoft.ML.AutoML.ExperimentResult<TMetrics> Execute (Microsoft.ML.IDataView trainData, string labelColumnName = "Label", string samplingKeyColumn = null, Microsoft.ML.IEstimator<Microsoft.ML.ITransformer> preFeaturizer = null, IProgress<Microsoft.ML.AutoML.RunDetail<TMetrics>> progressHandler = null);
member this.Execute : Microsoft.ML.IDataView * string * string * Microsoft.ML.IEstimator<Microsoft.ML.ITransformer> * IProgress<Microsoft.ML.AutoML.RunDetail<'Metrics>> -> Microsoft.ML.AutoML.ExperimentResult<'Metrics (requires 'Metrics : null)>
Public Function Execute (trainData As IDataView, Optional labelColumnName As String = "Label", Optional samplingKeyColumn As String = null, Optional preFeaturizer As IEstimator(Of ITransformer) = null, Optional progressHandler As IProgress(Of RunDetail(Of TMetrics)) = null) As ExperimentResult(Of TMetrics)

Parameters

trainData
IDataView IDataView IDataView

The training data used by the AutoML experiment.

labelColumnName
String String String

The dataset column used as the label.

samplingKeyColumn
String String String

The dataset column used as the sampling key column. See SamplingKeyColumnName for more information.

preFeaturizer
IEstimator<ITransformer>

Pre-featurizer that AutoML will apply to the data during an experiment. (The pre-featurizer will be fit only on the training data split to produce a trained transform. Then, the trained transform will be applied to both the training data split and corresponding validation data split.)

progressHandler
IProgress<RunDetail<TMetrics>>

A user-defined object that implements the IProgress<T> interface. AutoML will invoke the method Report(T) after each model it produces during the course of the experiment.

Returns

Remarks

Depending on the size of your data, the AutoML experiment could take a long time to execute.

Execute(IDataView, UInt32, ColumnInformation, IEstimator<ITransformer>, IProgress<CrossValidationRunDetail<TMetrics>>) Execute(IDataView, UInt32, ColumnInformation, IEstimator<ITransformer>, IProgress<CrossValidationRunDetail<TMetrics>>)

Executes an AutoML experiment.

public Microsoft.ML.AutoML.CrossValidationExperimentResult<TMetrics> Execute (Microsoft.ML.IDataView trainData, uint numberOfCVFolds, Microsoft.ML.AutoML.ColumnInformation columnInformation = null, Microsoft.ML.IEstimator<Microsoft.ML.ITransformer> preFeaturizer = null, IProgress<Microsoft.ML.AutoML.CrossValidationRunDetail<TMetrics>> progressHandler = null);
member this.Execute : Microsoft.ML.IDataView * uint32 * Microsoft.ML.AutoML.ColumnInformation * Microsoft.ML.IEstimator<Microsoft.ML.ITransformer> * IProgress<Microsoft.ML.AutoML.CrossValidationRunDetail<'Metrics>> -> Microsoft.ML.AutoML.CrossValidationExperimentResult<'Metrics (requires 'Metrics : null)>

Parameters

trainData
IDataView IDataView IDataView

The training data to be used by the AutoML experiment.

numberOfCVFolds
UInt32 UInt32 UInt32

The number of cross validation folds into which the training data should be divided when fitting a model.

columnInformation
ColumnInformation ColumnInformation ColumnInformation

Column information for the dataset.

preFeaturizer
IEstimator<ITransformer>

Pre-featurizer that AutoML will apply to the data during an experiment. (The pre-featurizer will be fit only on the training data split to produce a trained transform. Then, the trained transform will be applied to both the training data split and corresponding validation data split.)

progressHandler
IProgress<CrossValidationRunDetail<TMetrics>>

A user-defined object that implements the IProgress<T> interface. AutoML will invoke the method Report(T) after each model it produces during the course of the experiment.

Returns

Remarks

Depending on the size of your data, the AutoML experiment could take a long time to execute.

Execute(IDataView, UInt32, String, String, IEstimator<ITransformer>, Progress<CrossValidationRunDetail<TMetrics>>) Execute(IDataView, UInt32, String, String, IEstimator<ITransformer>, Progress<CrossValidationRunDetail<TMetrics>>) Execute(IDataView, UInt32, String, String, IEstimator<ITransformer>, Progress<CrossValidationRunDetail<TMetrics>>)

Executes an AutoML experiment.

public Microsoft.ML.AutoML.CrossValidationExperimentResult<TMetrics> Execute (Microsoft.ML.IDataView trainData, uint numberOfCVFolds, string labelColumnName = "Label", string samplingKeyColumn = null, Microsoft.ML.IEstimator<Microsoft.ML.ITransformer> preFeaturizer = null, Progress<Microsoft.ML.AutoML.CrossValidationRunDetail<TMetrics>> progressHandler = null);
member this.Execute : Microsoft.ML.IDataView * uint32 * string * string * Microsoft.ML.IEstimator<Microsoft.ML.ITransformer> * Progress<Microsoft.ML.AutoML.CrossValidationRunDetail<'Metrics>> -> Microsoft.ML.AutoML.CrossValidationExperimentResult<'Metrics (requires 'Metrics : null)>
Public Function Execute (trainData As IDataView, numberOfCVFolds As UInteger, Optional labelColumnName As String = "Label", Optional samplingKeyColumn As String = null, Optional preFeaturizer As IEstimator(Of ITransformer) = null, Optional progressHandler As Progress(Of CrossValidationRunDetail(Of TMetrics)) = null) As CrossValidationExperimentResult(Of TMetrics)

Parameters

trainData
IDataView IDataView IDataView

The training data to be used by the AutoML experiment.

numberOfCVFolds
UInt32 UInt32 UInt32

The number of cross validation folds into which the training data should be divided when fitting a model.

labelColumnName
String String String

The name of the label column.

samplingKeyColumn
String String String

The name of the sampling key column.

preFeaturizer
IEstimator<ITransformer>

Pre-featurizer that AutoML will apply to the data during an experiment. (The pre-featurizer will be fit only on the training data split to produce a trained transform. Then, the trained transform will be applied to both the training data split and corresponding validation data split.)

progressHandler
Progress<CrossValidationRunDetail<TMetrics>>

A user-defined object that implements the IProgress<T> interface. AutoML will invoke the method Report(T) after each model it produces during the course of the experiment.

Returns

Remarks

Depending on the size of your data, the AutoML experiment could take a long time to execute.

Applies to