Megosztás a következőn keresztül:


ImageClassification Class

Definition

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
ImageClassification
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.

Explicit Interface Implementations

IJsonModel<AutoMLVertical>.Create(Utf8JsonReader, ModelReaderWriterOptions)

Reads one JSON value (including objects or arrays) from the provided reader and converts it to a model.

(Inherited from AutoMLVertical)
IJsonModel<AutoMLVertical>.Write(Utf8JsonWriter, ModelReaderWriterOptions)

Writes the model to the provided Utf8JsonWriter.

(Inherited from AutoMLVertical)
IJsonModel<ImageClassification>.Create(Utf8JsonReader, ModelReaderWriterOptions)

Reads one JSON value (including objects or arrays) from the provided reader and converts it to a model.

IJsonModel<ImageClassification>.Write(Utf8JsonWriter, ModelReaderWriterOptions)

Writes the model to the provided Utf8JsonWriter.

IPersistableModel<AutoMLVertical>.Create(BinaryData, ModelReaderWriterOptions)

Converts the provided BinaryData into a model.

(Inherited from AutoMLVertical)
IPersistableModel<AutoMLVertical>.GetFormatFromOptions(ModelReaderWriterOptions)

Gets the data interchange format (JSON, Xml, etc) that the model uses when communicating with the service.

(Inherited from AutoMLVertical)
IPersistableModel<AutoMLVertical>.Write(ModelReaderWriterOptions)

Writes the model into a BinaryData.

(Inherited from AutoMLVertical)
IPersistableModel<ImageClassification>.Create(BinaryData, ModelReaderWriterOptions)

Converts the provided BinaryData into a model.

IPersistableModel<ImageClassification>.GetFormatFromOptions(ModelReaderWriterOptions)

Gets the data interchange format (JSON, Xml, etc) that the model uses when communicating with the service.

IPersistableModel<ImageClassification>.Write(ModelReaderWriterOptions)

Writes the model into a BinaryData.

Applies to