IRegression Interface

Definition

Namespace:

Microsoft.Azure.PowerShell.Cmdlets.MachineLearningServices.Models.Api20240401

Assembly:

Az.MachineLearningServices.private.dll

[System.ComponentModel.TypeConverter(typeof(Microsoft.Azure.PowerShell.Cmdlets.MachineLearningServices.Models.Api20240401.RegressionTypeConverter))]
public interface IRegression : Microsoft.Azure.PowerShell.Cmdlets.MachineLearningServices.Models.Api20240401.IAutoMlVertical, Microsoft.Azure.PowerShell.Cmdlets.MachineLearningServices.Models.Api20240401.ITableVertical

[<System.ComponentModel.TypeConverter(typeof(Microsoft.Azure.PowerShell.Cmdlets.MachineLearningServices.Models.Api20240401.RegressionTypeConverter))>]
type IRegression = interface
    interface IJsonSerializable
    interface ITableVertical
    interface IAutoMlVertical

Public Interface IRegression
Implements IAutoMlVertical, ITableVertical

Derived

Microsoft.Azure.PowerShell.Cmdlets.MachineLearningServices.Models.Api20240401.Regression

Attributes

TypeConverterAttribute

Implements

IAutoMlVertical ITableVertical IJsonSerializable

Properties

CvSplitColumnName	Columns to use for CVSplit data. (Inherited from ITableVertical)
FeaturizationSettingBlockedTransformer	These transformers shall not be used in featurization. (Inherited from ITableVertical)
FeaturizationSettingColumnNameAndType	Dictionary of column name and its type (int, float, string, datetime etc). (Inherited from ITableVertical)
FeaturizationSettingDatasetLanguage	Dataset language, useful for the text data. (Inherited from ITableVertical)
FeaturizationSettingEnableDnnFeaturization	Determines whether to use Dnn based featurizers for data featurization. (Inherited from ITableVertical)
FeaturizationSettingMode	Featurization mode - User can keep the default 'Auto' mode and AutoML will take care of necessary transformation of the data in featurization phase. If 'Off' is selected then no featurization is done. If 'Custom' is selected then user can specify additional inputs to customize how featurization is done. (Inherited from ITableVertical)
FeaturizationSettingTransformerParam	User can specify additional transformers to be used along with the columns to which it would be applied and parameters for the transformer constructor. (Inherited from ITableVertical)
LimitSettingEnableEarlyTermination	Enable early termination, determines whether or not if AutoMLJob will terminate early if there is no score improvement in last 20 iterations. (Inherited from ITableVertical)
LimitSettingExitScore	Exit score for the AutoML job. (Inherited from ITableVertical)
LimitSettingMaxConcurrentTrial	Maximum Concurrent iterations. (Inherited from ITableVertical)
LimitSettingMaxCoresPerTrial	Max cores per iteration. (Inherited from ITableVertical)
LimitSettingMaxTrial	Number of iterations. (Inherited from ITableVertical)
LimitSettingTimeout	AutoML job timeout. (Inherited from ITableVertical)
LimitSettingTrialTimeout	Iteration timeout. (Inherited from ITableVertical)
LogVerbosity	Log verbosity for the job. (Inherited from IAutoMlVertical)
NCrossValidationMode	[Required] Mode for determining N-Cross validations. (Inherited from ITableVertical)
PrimaryMetric	Primary metric for regression task.
TargetColumnName	Target column name: This is prediction values column. Also known as label column name in context of classification tasks. (Inherited from IAutoMlVertical)
TaskType	[Required] Task type for AutoMLJob. (Inherited from IAutoMlVertical)
TestDataDescription	Description for the input. (Inherited from ITableVertical)
TestDataJobInputType	[Required] Specifies the type of job. (Inherited from ITableVertical)
TestDataMode	Input Asset Delivery Mode. (Inherited from ITableVertical)
TestDataSize	The fraction of test dataset that needs to be set aside for validation purpose. Values between (0.0 , 1.0) Applied when validation dataset is not provided. (Inherited from ITableVertical)
TestDataUri	[Required] Input Asset URI. (Inherited from ITableVertical)
TrainingDataDescription	Description for the input. (Inherited from IAutoMlVertical)
TrainingDataJobInputType	[Required] Specifies the type of job. (Inherited from IAutoMlVertical)
TrainingDataMode	Input Asset Delivery Mode. (Inherited from IAutoMlVertical)
TrainingDataUri	[Required] Input Asset URI. (Inherited from IAutoMlVertical)
TrainingSettingAllowedTrainingAlgorithm	Allowed models for regression task.
TrainingSettingBlockedTrainingAlgorithm	Blocked models for regression task.
TrainingSettingEnableDnnTraining	Enable recommendation of DNN models.
TrainingSettingEnableModelExplainability	Flag to turn on explainability on best model.
TrainingSettingEnableOnnxCompatibleModel	Flag for enabling onnx compatible models.
TrainingSettingEnableStackEnsemble	Enable stack ensemble run.
TrainingSettingEnableVoteEnsemble	Enable voting ensemble run.
TrainingSettingEnsembleModelDownloadTimeout	During VotingEnsemble and StackEnsemble model generation, multiple fitted models from the previous child runs are downloaded. Configure this parameter with a higher value than 300 secs, if more time is needed.
TrainingSettingStackEnsembleSettingStackMetaLearnerKWarg	Optional parameters to pass to the initializer of the meta-learner.
TrainingSettingStackEnsembleSettingStackMetaLearnerTrainPercentage	Specifies the proportion of the training set (when choosing train and validation type of training) to be reserved for training the meta-learner. Default value is 0.2.
TrainingSettingStackEnsembleSettingStackMetaLearnerType	The meta-learner is a model trained on the output of the individual heterogeneous models.
ValidationDataDescription	Description for the input. (Inherited from ITableVertical)
ValidationDataJobInputType	[Required] Specifies the type of job. (Inherited from ITableVertical)
ValidationDataMode	Input Asset Delivery Mode. (Inherited from ITableVertical)
ValidationDataSize	The fraction of training dataset that needs to be set aside for validation purpose. Values between (0.0 , 1.0) Applied when validation dataset is not provided. (Inherited from ITableVertical)
ValidationDataUri	[Required] Input Asset URI. (Inherited from ITableVertical)
WeightColumnName	The name of the sample weight column. Automated ML supports a weighted column as an input, causing rows in the data to be weighted up or down. (Inherited from ITableVertical)

Methods

ToJson(JsonObject, SerializationMode)

(Inherited from IJsonSerializable)