AI Platform Data Labeling Service V1beta1 API - Class Google::Cloud::DataLabeling::V1beta1::EvaluationJob (v0.9.0)

Reference documentation and code samples for the AI Platform Data Labeling Service V1beta1 API class Google::Cloud::DataLabeling::V1beta1::EvaluationJob.

Defines an evaluation job that runs periodically to generate Evaluations. Creating an evaluation job is the starting point for using continuous evaluation.

Inherits

  • Object

Extended By

  • Google::Protobuf::MessageExts::ClassMethods

Includes

  • Google::Protobuf::MessageExts

Methods

#annotation_spec_set

def annotation_spec_set() -> ::String
Returns
  • (::String) — Required. Name of the AnnotationSpecSet describing all the labels that your machine learning model outputs. You must create this resource before you create an evaluation job and provide its name in the following format:

    "projects/{project_id}/annotationSpecSets/{annotation_spec_set_id}"

#annotation_spec_set=

def annotation_spec_set=(value) -> ::String
Parameter
  • value (::String) — Required. Name of the AnnotationSpecSet describing all the labels that your machine learning model outputs. You must create this resource before you create an evaluation job and provide its name in the following format:

    "projects/{project_id}/annotationSpecSets/{annotation_spec_set_id}"

Returns
  • (::String) — Required. Name of the AnnotationSpecSet describing all the labels that your machine learning model outputs. You must create this resource before you create an evaluation job and provide its name in the following format:

    "projects/{project_id}/annotationSpecSets/{annotation_spec_set_id}"

#attempts

def attempts() -> ::Array<::Google::Cloud::DataLabeling::V1beta1::Attempt>
Returns

#attempts=

def attempts=(value) -> ::Array<::Google::Cloud::DataLabeling::V1beta1::Attempt>
Parameter
Returns

#create_time

def create_time() -> ::Google::Protobuf::Timestamp
Returns

#create_time=

def create_time=(value) -> ::Google::Protobuf::Timestamp
Parameter
Returns

#description

def description() -> ::String
Returns
  • (::String) — Required. Description of the job. The description can be up to 25,000 characters long.

#description=

def description=(value) -> ::String
Parameter
  • value (::String) — Required. Description of the job. The description can be up to 25,000 characters long.
Returns
  • (::String) — Required. Description of the job. The description can be up to 25,000 characters long.

#evaluation_job_config

def evaluation_job_config() -> ::Google::Cloud::DataLabeling::V1beta1::EvaluationJobConfig
Returns

#evaluation_job_config=

def evaluation_job_config=(value) -> ::Google::Cloud::DataLabeling::V1beta1::EvaluationJobConfig
Parameter
Returns

#label_missing_ground_truth

def label_missing_ground_truth() -> ::Boolean
Returns
  • (::Boolean) — Required. Whether you want Data Labeling Service to provide ground truth labels for prediction input. If you want the service to assign human labelers to annotate your data, set this to true. If you want to provide your own ground truth labels in the evaluation job's BigQuery table, set this to false.

#label_missing_ground_truth=

def label_missing_ground_truth=(value) -> ::Boolean
Parameter
  • value (::Boolean) — Required. Whether you want Data Labeling Service to provide ground truth labels for prediction input. If you want the service to assign human labelers to annotate your data, set this to true. If you want to provide your own ground truth labels in the evaluation job's BigQuery table, set this to false.
Returns
  • (::Boolean) — Required. Whether you want Data Labeling Service to provide ground truth labels for prediction input. If you want the service to assign human labelers to annotate your data, set this to true. If you want to provide your own ground truth labels in the evaluation job's BigQuery table, set this to false.

#model_version

def model_version() -> ::String
Returns
  • (::String) — Required. The AI Platform Prediction model version to be evaluated. Prediction input and output is sampled from this model version. When creating an evaluation job, specify the model version in the following format:

    "projects/{project_id}/models/{model_name}/versions/{version_name}"

    There can only be one evaluation job per model version.

#model_version=

def model_version=(value) -> ::String
Parameter
  • value (::String) — Required. The AI Platform Prediction model version to be evaluated. Prediction input and output is sampled from this model version. When creating an evaluation job, specify the model version in the following format:

    "projects/{project_id}/models/{model_name}/versions/{version_name}"

    There can only be one evaluation job per model version.

Returns
  • (::String) — Required. The AI Platform Prediction model version to be evaluated. Prediction input and output is sampled from this model version. When creating an evaluation job, specify the model version in the following format:

    "projects/{project_id}/models/{model_name}/versions/{version_name}"

    There can only be one evaluation job per model version.

#name

def name() -> ::String
Returns
  • (::String) — Output only. After you create a job, Data Labeling Service assigns a name to the job with the following format:

    "projects/{project_id}/evaluationJobs/{evaluation_job_id}"

#name=

def name=(value) -> ::String
Parameter
  • value (::String) — Output only. After you create a job, Data Labeling Service assigns a name to the job with the following format:

    "projects/{project_id}/evaluationJobs/{evaluation_job_id}"

Returns
  • (::String) — Output only. After you create a job, Data Labeling Service assigns a name to the job with the following format:

    "projects/{project_id}/evaluationJobs/{evaluation_job_id}"

#schedule

def schedule() -> ::String
Returns
  • (::String) — Required. Describes the interval at which the job runs. This interval must be at least 1 day, and it is rounded to the nearest day. For example, if you specify a 50-hour interval, the job runs every 2 days.

    You can provide the schedule in crontab format or in an English-like format.

    Regardless of what you specify, the job will run at 10:00 AM UTC. Only the interval from this schedule is used, not the specific time of day.

#schedule=

def schedule=(value) -> ::String
Parameter
  • value (::String) — Required. Describes the interval at which the job runs. This interval must be at least 1 day, and it is rounded to the nearest day. For example, if you specify a 50-hour interval, the job runs every 2 days.

    You can provide the schedule in crontab format or in an English-like format.

    Regardless of what you specify, the job will run at 10:00 AM UTC. Only the interval from this schedule is used, not the specific time of day.

Returns
  • (::String) — Required. Describes the interval at which the job runs. This interval must be at least 1 day, and it is rounded to the nearest day. For example, if you specify a 50-hour interval, the job runs every 2 days.

    You can provide the schedule in crontab format or in an English-like format.

    Regardless of what you specify, the job will run at 10:00 AM UTC. Only the interval from this schedule is used, not the specific time of day.

#state

def state() -> ::Google::Cloud::DataLabeling::V1beta1::EvaluationJob::State
Returns

#state=

def state=(value) -> ::Google::Cloud::DataLabeling::V1beta1::EvaluationJob::State
Parameter
Returns