ClassificationTask Class
Definition
Important
Some information relates to prerelease product that may be substantially modified before it’s released. Microsoft makes no warranties, express or implied, with respect to the information provided here.
Classification task in AutoML Table vertical.
public class ClassificationTask : Azure.ResourceManager.MachineLearning.Models.AutoMLVertical, System.ClientModel.Primitives.IJsonModel<Azure.ResourceManager.MachineLearning.Models.ClassificationTask>, System.ClientModel.Primitives.IPersistableModel<Azure.ResourceManager.MachineLearning.Models.ClassificationTask>public class ClassificationTask : Azure.ResourceManager.MachineLearning.Models.AutoMLVerticaltype ClassificationTask = class
inherit AutoMLVertical
interface IJsonModel<ClassificationTask>
interface IPersistableModel<ClassificationTask>type ClassificationTask = class
inherit AutoMLVerticalPublic Class ClassificationTask
Inherits AutoMLVertical
Implements IJsonModel(Of ClassificationTask), IPersistableModel(Of ClassificationTask)Public Class ClassificationTask
Inherits AutoMLVertical- Inheritance
- Implements
Constructors
| ClassificationTask(MachineLearningTableJobInput) |
Initializes a new instance of ClassificationTask. |
Properties
| CvSplitColumnNames |
Columns to use for CVSplit data. |
| FeaturizationSettings |
Featurization inputs needed for AutoML job. |
| FixedParameters |
Model/training parameters that will remain constant throughout training. |
| LimitSettings |
Execution constraints for AutoMLJob. |
| LogVerbosity |
Log verbosity for the job. (Inherited from AutoMLVertical) |
| NCrossValidations |
Number of cross validation folds to be applied on training dataset when validation dataset is not provided. Please note NCrossValidations is the base class. According to the scenario, a derived class of the base class might need to be assigned here, or this property needs to be casted to one of the possible derived classes. The available derived classes include AutoNCrossValidations and CustomNCrossValidations. |
| PositiveLabel |
Positive label for binary metrics calculation. |
| PrimaryMetric |
Primary metric for the task. |
| SearchSpace |
Search space for sampling different combinations of models and their hyperparameters. |
| SweepSettings |
Settings for model sweeping and hyperparameter tuning. |
| TargetColumnName |
Target column name: This is prediction values column. Also known as label column name in context of classification tasks. (Inherited from AutoMLVertical) |
| TestData |
Test data input. |
| 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. |
| TrainingData |
[Required] Training data input. (Inherited from AutoMLVertical) |
| TrainingSettings |
Inputs for training phase for an AutoML Job. |
| ValidationData |
Validation data inputs. |
| 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. |
| 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. |
