Microsoft.ML.AutoML Namespace
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Classes
ArrayMath | |
AutoCatalog |
A catalog of all available AutoML tasks. |
AutoMLExperiment |
The class for AutoML experiment |
AutoMLExperiment.AutoMLExperimentSettings | |
AutoMLExperimentExtension | |
BinaryClassificationExperiment |
AutoML experiment on binary classification datasets. |
BinaryExperimentSettings |
Settings for AutoML experiments on binary classification datasets. |
ColumnInferenceResults |
Contains information AutoML inferred about columns in a dataset. |
ColumnInformation |
Information about the columns in a dataset. |
CrossValidationExperimentResult<TMetrics> |
Result of an AutoML experiment that includes cross validation details. |
CrossValidationRunDetail<TMetrics> |
Details about a cross validation run in an AutoML experiment. |
DefaultPerformanceMonitor | |
Entity | |
Estimator | |
ExperimentBase<TMetrics,TExperimentSettings> |
AutoML experiment base class. All task-specific AutoML experiments (like BinaryClassificationExperiment) inherit from this class. |
ExperimentResult<TMetrics> |
Result of an AutoML experiment. |
ExperimentSettings |
Base class for experiment settings. All task-specific AutoML experiment settings (like BinaryExperimentSettings) inherit from this class. |
FairnessTrialResult | |
InferenceException |
Exception thrown by AutoML. |
MLContextExtension |
Class containing AutoML extension methods to MLContext |
MulticlassClassificationExperiment |
AutoML experiment on multiclass classification datasets. |
MulticlassExperimentSettings |
Settings for AutoML experiments on multiclass classification datasets. |
RankingExperiment |
AutoML experiment on ranking datasets. |
RankingExperimentResultExtensions |
Extension methods that operate over ranking experiment run results. |
RankingExperimentSettings | |
RecommendationExperiment |
AutoML experiment on recommendation datasets. |
RecommendationExperimentSettings |
Settings for AutoML experiments on recommendation datasets. |
RegressionExperiment |
AutoML experiment on regression classification datasets. |
RegressionExperimentResultExtensions |
Extension methods that operate over regression experiment run results. |
RegressionExperimentSettings |
Settings for AutoML experiments on regression datasets. |
RunDetail |
Details about an AutoML experiment run. |
RunDetail<TMetrics> |
Details about an AutoML experiment run. |
SweepableEstimator |
Estimator with search space. |
SweepableExtension | |
SweepablePipeline | |
TrainResult<TMetrics> |
Result of a pipeline trained on a cross validation fold. |
TrialPerformanceMetrics |
Performance metrics for a trial. |
TrialResult | |
TrialSettings |
Settings used for the trial |
Interfaces
ICrossValidateDatasetManager |
Inferface for cross validate dataset manager. |
IDatasetManager |
Interface for dataset manager. This interface doesn't include any method or property definition and is used by AutoMLExperiment and other components to retrieve the instance of the actual dataset manager from containers. |
IEvaluateMetricManager | |
IMetricManager |
Interface for metric manager. |
IMonitor |
instance for monitor, which is used by AutoMLExperiment to report training progress. |
IPerformanceMonitor | |
ISweepable | |
ISweepable<T> | |
ITrainValidateDatasetManager | |
ITrialRunner |
interface for all trial runners. |
ITuner |
Enums
BinaryClassificationMetric |
Binary classification metric that AutoML will aim to optimize in its sweeping process during an experiment. |
BinaryClassificationTrainer |
Enumeration of ML.NET binary classification trainers used by AutoML. |
CacheBeforeTrainer |
Whether AutoML should cache before ML.NET trainers. See WantCaching for more information on caching. |
InferenceExceptionType |
Type of exception encountered by AutoML. |
MulticlassClassificationMetric |
Multiclass classification metric that AutoML will aim to optimize in its sweeping process during an experiment. |
MulticlassClassificationTrainer |
Enumeration of ML.NET multiclass classification trainers used by AutoML. |
RankingMetric | |
RankingTrainer |
Enumeration of ML.NET ranking trainers used by AutoML. |
RecommendationTrainer |
Enumeration of ML.NET recommendation trainers used by AutoML. |
RegressionMetric |
Regression metric that AutoML will aim to optimize in its sweeping process during an experiment. |
RegressionTrainer |
Enumeration of ML.NET multiclass classification trainers used by AutoML. |