ImageClassification Class
Definition
Important
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Image Classification. Multi-class image classification is used when an image is classified with only a single label from a set of classes - e.g. each image is classified as either an image of a 'cat' or a 'dog' or a 'duck'.
public class ImageClassification : Azure.ResourceManager.MachineLearning.Models.AutoMLVertical, System.ClientModel.Primitives.IJsonModel<Azure.ResourceManager.MachineLearning.Models.ImageClassification>, System.ClientModel.Primitives.IPersistableModel<Azure.ResourceManager.MachineLearning.Models.ImageClassification>
public class ImageClassification : Azure.ResourceManager.MachineLearning.Models.AutoMLVertical
type ImageClassification = class
inherit AutoMLVertical
interface IJsonModel<ImageClassification>
interface IPersistableModel<ImageClassification>
type ImageClassification = class
inherit AutoMLVertical
Public Class ImageClassification
Inherits AutoMLVertical
Implements IJsonModel(Of ImageClassification), IPersistableModel(Of ImageClassification)
Public Class ImageClassification
Inherits AutoMLVertical
- Inheritance
- Implements
Constructors
ImageClassification(MachineLearningTableJobInput, ImageLimitSettings) |
Initializes a new instance of ImageClassification. |
Properties
LimitSettings |
[Required] Limit settings for the AutoML job. |
LogVerbosity |
Log verbosity for the job. (Inherited from AutoMLVertical) |
ModelSettings |
Settings used for training the model. |
PrimaryMetric |
Primary metric to optimize for this task. |
SearchSpace |
Search space for sampling different combinations of models and their hyperparameters. |
SweepSettings |
Model sweeping and hyperparameter sweeping related settings. |
TargetColumnName |
Target column name: This is prediction values column. Also known as label column name in context of classification tasks. (Inherited from AutoMLVertical) |
TrainingData |
[Required] Training data input. (Inherited from AutoMLVertical) |
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. |