Interface ModelsCreateParams

interface ModelsCreateParams {
    contentLocation?: WatsonXAI.ContentLocation;
    custom?: WatsonXAI.JsonObject;
    dataPreprocessing?: WatsonXAI.DataPreprocessingTransformation[];
    description?: string;
    domain?: string;
    foundationModel?: WatsonXAI.BaseModel;
    headers?: OutgoingHttpHeaders;
    hybridPipelineSoftwareSpecs?: WatsonXAI.SoftwareSpecRel[];
    hyperParameters?: WatsonXAI.JsonObject;
    labelColumn?: string;
    metrics?: WatsonXAI.Metric[];
    modelDefinition?: WatsonXAI.ModelDefinitionId;
    modelVersion?: WatsonXAI.ModelEntityModelVersion;
    name: string;
    pipeline?: WatsonXAI.Rel;
    projectId?: string;
    schemas?: WatsonXAI.ModelEntitySchemas;
    signal?: AbortSignal;
    size?: WatsonXAI.ModelEntitySize;
    softwareSpec?: WatsonXAI.SoftwareSpecRel;
    spaceId?: string;
    tags?: string[];
    testDataReferences?: WatsonXAI.DataConnectionReference[];
    training?: WatsonXAI.TrainingDetails;
    trainingDataReferences?: WatsonXAI.DataConnectionReference[];
    trainingId?: string;
    transformedLabelColumn?: string;
    type: string;
    userDefinedObjects?: WatsonXAI.JsonObject;
}

Hierarchy

  • DefaultParams
    • ModelsCreateParams

Properties

contentLocation? custom? dataPreprocessing? description? domain? foundationModel? headers? hybridPipelineSoftwareSpecs? hyperParameters? labelColumn? metrics? modelDefinition? modelVersion? name pipeline? projectId? schemas? signal? size? softwareSpec? spaceId? tags? testDataReferences? training? trainingDataReferences? trainingId? transformedLabelColumn? type userDefinedObjects?

Properties

Optional contentLocation

contentLocation?: WatsonXAI.ContentLocation

Details about the attachments that should be uploaded with this model.

Optional custom

custom?: WatsonXAI.JsonObject

User defined properties specified as key-value pairs.

Optional dataPreprocessing

dataPreprocessing?: WatsonXAI.DataPreprocessingTransformation[]

An optional array which contains the data preprocessing transformations that were executed by the training job that created this model.

Optional description

description?: string

A description of the resource.

Optional domain

domain?: string

User provided domain name for this model. For example: sentiment, entity, visual-recognition, finance, retail, real estate etc.

Optional foundationModel

foundationModel?: WatsonXAI.BaseModel

The model id of the base model for this job.

Optional headers

headers?: OutgoingHttpHeaders

Optional hybridPipelineSoftwareSpecs

hybridPipelineSoftwareSpecs?: WatsonXAI.SoftwareSpecRel[]

The list of the software specifications that are used by the pipeline that generated this model, if the model was generated by a pipeline.

Optional hyperParameters

hyperParameters?: WatsonXAI.JsonObject

Hyper parameters used for training this model.

Optional labelColumn

labelColumn?: string

The name of the label column.

Optional metrics

metrics?: WatsonXAI.Metric[]

Metrics that can be returned by an operation.

Optional modelDefinition

modelDefinition?: WatsonXAI.ModelDefinitionId

The model definition.

Optional modelVersion

modelVersion?: WatsonXAI.ModelEntityModelVersion

Optional metadata that can be used to provide information about this model that can be tracked with IBM AI Factsheets. See Using AI Factsheets for more details.

name

name: string

The name of the resource.

Optional pipeline

pipeline?: WatsonXAI.Rel

A reference to a resource.

Optional projectId

projectId?: string

The project that contains the resource. Either space_id or project_id has to be given.

Optional schemas

schemas?: WatsonXAI.ModelEntitySchemas

If the prediction schemas are provided here then they take precedent over any schemas provided in the data references. Note that data references contain the schema for the associated data and this object contains the schema(s) for the associated prediction, if any. In the case that the prediction input data matches exactly the schema of the training data references then the prediction schema can be omitted. However it is highly recommended to always specify the prediction schemas using this field.

Optional signal

signal?: AbortSignal

Optional size

size?: WatsonXAI.ModelEntitySize

This will be used by scoring to record the size of the model.

Optional softwareSpec

softwareSpec?: WatsonXAI.SoftwareSpecRel

A software specification.

Optional spaceId

spaceId?: string

The space that contains the resource. Either space_id or project_id has to be given.

Optional tags

tags?: string[]

A list of tags for this resource.

Optional testDataReferences

testDataReferences?: WatsonXAI.DataConnectionReference[]

The holdout/test datasets.

Optional training

training?: WatsonXAI.TrainingDetails

Information about the training job that created this model.

Optional trainingDataReferences

trainingDataReferences?: WatsonXAI.DataConnectionReference[]

The training data that was used to create this model.

Optional trainingId

trainingId?: string

Deprecated: this is replaced by training.id. This field can be used to store the id of the training job that was used to produce this model.

Optional transformedLabelColumn

transformedLabelColumn?: string

The name of the label column seen by the estimator, which may have been transformed by the previous transformers in the pipeline. This is not necessarily the same column as the label_column in the initial data set.

type

type: string

The model type. The supported model types can be found in the documentation here.

Optional userDefinedObjects

userDefinedObjects?: WatsonXAI.JsonObject

User defined objects referenced by the model. For any user defined class or function used in the model, its name, as referenced in the model, must be specified as the key and its fully qualified class or function name must be specified as the value. This is applicable for Tensorflow 2.X models serialized in H5 format using the tf.keras API.

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contentLocationcustomdataPreprocessingdescriptiondomainfoundationModelheadershybridPipelineSoftwareSpecshyperParameterslabelColumnmetricsmodelDefinitionmodelVersionnamepipelineprojectIdschemassignalsizesoftwareSpecspaceIdtagstestDataReferencestrainingtrainingDataReferencestrainingIdtransformedLabelColumntypeuserDefinedObjects