Class: Aws::LookoutEquipment::Client
- Inherits:
-
Seahorse::Client::Base
- Object
- Seahorse::Client::Base
- Aws::LookoutEquipment::Client
- Includes:
- ClientStubs
- Defined in:
- gems/aws-sdk-lookoutequipment/lib/aws-sdk-lookoutequipment/client.rb
Overview
An API client for LookoutEquipment. To construct a client, you need to configure a :region
and :credentials
.
client = Aws::LookoutEquipment::Client.new(
region: region_name,
credentials: credentials,
# ...
)
For details on configuring region and credentials see the developer guide.
See #initialize for a full list of supported configuration options.
Instance Attribute Summary
Attributes inherited from Seahorse::Client::Base
API Operations collapse
-
#create_dataset(params = {}) ⇒ Types::CreateDatasetResponse
Creates a container for a collection of data being ingested for analysis.
-
#create_inference_scheduler(params = {}) ⇒ Types::CreateInferenceSchedulerResponse
Creates a scheduled inference.
-
#create_label(params = {}) ⇒ Types::CreateLabelResponse
Creates a label for an event.
-
#create_label_group(params = {}) ⇒ Types::CreateLabelGroupResponse
Creates a group of labels.
-
#create_model(params = {}) ⇒ Types::CreateModelResponse
Creates a machine learning model for data inference.
-
#create_retraining_scheduler(params = {}) ⇒ Types::CreateRetrainingSchedulerResponse
Creates a retraining scheduler on the specified model.
-
#delete_dataset(params = {}) ⇒ Struct
Deletes a dataset and associated artifacts.
-
#delete_inference_scheduler(params = {}) ⇒ Struct
Deletes an inference scheduler that has been set up.
-
#delete_label(params = {}) ⇒ Struct
Deletes a label.
-
#delete_label_group(params = {}) ⇒ Struct
Deletes a group of labels.
-
#delete_model(params = {}) ⇒ Struct
Deletes a machine learning model currently available for Amazon Lookout for Equipment.
-
#delete_resource_policy(params = {}) ⇒ Struct
Deletes the resource policy attached to the resource.
-
#delete_retraining_scheduler(params = {}) ⇒ Struct
Deletes a retraining scheduler from a model.
-
#describe_data_ingestion_job(params = {}) ⇒ Types::DescribeDataIngestionJobResponse
Provides information on a specific data ingestion job such as creation time, dataset ARN, and status.
-
#describe_dataset(params = {}) ⇒ Types::DescribeDatasetResponse
Provides a JSON description of the data in each time series dataset, including names, column names, and data types.
-
#describe_inference_scheduler(params = {}) ⇒ Types::DescribeInferenceSchedulerResponse
Specifies information about the inference scheduler being used, including name, model, status, and associated metadata.
-
#describe_label(params = {}) ⇒ Types::DescribeLabelResponse
Returns the name of the label.
-
#describe_label_group(params = {}) ⇒ Types::DescribeLabelGroupResponse
Returns information about the label group.
-
#describe_model(params = {}) ⇒ Types::DescribeModelResponse
Provides a JSON containing the overall information about a specific machine learning model, including model name and ARN, dataset, training and evaluation information, status, and so on.
-
#describe_model_version(params = {}) ⇒ Types::DescribeModelVersionResponse
Retrieves information about a specific machine learning model version.
-
#describe_resource_policy(params = {}) ⇒ Types::DescribeResourcePolicyResponse
Provides the details of a resource policy attached to a resource.
-
#describe_retraining_scheduler(params = {}) ⇒ Types::DescribeRetrainingSchedulerResponse
Provides a description of the retraining scheduler, including information such as the model name and retraining parameters.
-
#import_dataset(params = {}) ⇒ Types::ImportDatasetResponse
Imports a dataset.
-
#import_model_version(params = {}) ⇒ Types::ImportModelVersionResponse
Imports a model that has been trained successfully.
-
#list_data_ingestion_jobs(params = {}) ⇒ Types::ListDataIngestionJobsResponse
Provides a list of all data ingestion jobs, including dataset name and ARN, S3 location of the input data, status, and so on.
-
#list_datasets(params = {}) ⇒ Types::ListDatasetsResponse
Lists all datasets currently available in your account, filtering on the dataset name.
-
#list_inference_events(params = {}) ⇒ Types::ListInferenceEventsResponse
Lists all inference events that have been found for the specified inference scheduler.
-
#list_inference_executions(params = {}) ⇒ Types::ListInferenceExecutionsResponse
Lists all inference executions that have been performed by the specified inference scheduler.
-
#list_inference_schedulers(params = {}) ⇒ Types::ListInferenceSchedulersResponse
Retrieves a list of all inference schedulers currently available for your account.
-
#list_label_groups(params = {}) ⇒ Types::ListLabelGroupsResponse
Returns a list of the label groups.
-
#list_labels(params = {}) ⇒ Types::ListLabelsResponse
Provides a list of labels.
-
#list_model_versions(params = {}) ⇒ Types::ListModelVersionsResponse
Generates a list of all model versions for a given model, including the model version, model version ARN, and status.
-
#list_models(params = {}) ⇒ Types::ListModelsResponse
Generates a list of all models in the account, including model name and ARN, dataset, and status.
-
#list_retraining_schedulers(params = {}) ⇒ Types::ListRetrainingSchedulersResponse
Lists all retraining schedulers in your account, filtering by model name prefix and status.
-
#list_sensor_statistics(params = {}) ⇒ Types::ListSensorStatisticsResponse
Lists statistics about the data collected for each of the sensors that have been successfully ingested in the particular dataset.
-
#list_tags_for_resource(params = {}) ⇒ Types::ListTagsForResourceResponse
Lists all the tags for a specified resource, including key and value.
-
#put_resource_policy(params = {}) ⇒ Types::PutResourcePolicyResponse
Creates a resource control policy for a given resource.
-
#start_data_ingestion_job(params = {}) ⇒ Types::StartDataIngestionJobResponse
Starts a data ingestion job.
-
#start_inference_scheduler(params = {}) ⇒ Types::StartInferenceSchedulerResponse
Starts an inference scheduler.
-
#start_retraining_scheduler(params = {}) ⇒ Types::StartRetrainingSchedulerResponse
Starts a retraining scheduler.
-
#stop_inference_scheduler(params = {}) ⇒ Types::StopInferenceSchedulerResponse
Stops an inference scheduler.
-
#stop_retraining_scheduler(params = {}) ⇒ Types::StopRetrainingSchedulerResponse
Stops a retraining scheduler.
-
#tag_resource(params = {}) ⇒ Struct
Associates a given tag to a resource in your account.
-
#untag_resource(params = {}) ⇒ Struct
Removes a specific tag from a given resource.
-
#update_active_model_version(params = {}) ⇒ Types::UpdateActiveModelVersionResponse
Sets the active model version for a given machine learning model.
-
#update_inference_scheduler(params = {}) ⇒ Struct
Updates an inference scheduler.
-
#update_label_group(params = {}) ⇒ Struct
Updates the label group.
-
#update_model(params = {}) ⇒ Struct
Updates a model in the account.
-
#update_retraining_scheduler(params = {}) ⇒ Struct
Updates a retraining scheduler.
Instance Method Summary collapse
-
#initialize(options) ⇒ Client
constructor
A new instance of Client.
Methods included from ClientStubs
#api_requests, #stub_data, #stub_responses
Methods inherited from Seahorse::Client::Base
add_plugin, api, clear_plugins, define, new, #operation_names, plugins, remove_plugin, set_api, set_plugins
Methods included from Seahorse::Client::HandlerBuilder
#handle, #handle_request, #handle_response
Constructor Details
#initialize(options) ⇒ Client
Returns a new instance of Client.
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# File 'gems/aws-sdk-lookoutequipment/lib/aws-sdk-lookoutequipment/client.rb', line 451 def initialize(*args) super end |
Instance Method Details
#create_dataset(params = {}) ⇒ Types::CreateDatasetResponse
Creates a container for a collection of data being ingested for analysis. The dataset contains the metadata describing where the data is and what the data actually looks like. For example, it contains the location of the data source, the data schema, and other information. A dataset also contains any tags associated with the ingested data.
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# File 'gems/aws-sdk-lookoutequipment/lib/aws-sdk-lookoutequipment/client.rb', line 517 def create_dataset(params = {}, = {}) req = build_request(:create_dataset, params) req.send_request() end |
#create_inference_scheduler(params = {}) ⇒ Types::CreateInferenceSchedulerResponse
Creates a scheduled inference. Scheduling an inference is setting up a continuous real-time inference plan to analyze new measurement data. When setting up the schedule, you provide an S3 bucket location for the input data, assign it a delimiter between separate entries in the data, set an offset delay if desired, and set the frequency of inferencing. You must also provide an S3 bucket location for the output data.
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# File 'gems/aws-sdk-lookoutequipment/lib/aws-sdk-lookoutequipment/client.rb', line 649 def create_inference_scheduler(params = {}, = {}) req = build_request(:create_inference_scheduler, params) req.send_request() end |
#create_label(params = {}) ⇒ Types::CreateLabelResponse
Creates a label for an event.
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# File 'gems/aws-sdk-lookoutequipment/lib/aws-sdk-lookoutequipment/client.rb', line 722 def create_label(params = {}, = {}) req = build_request(:create_label, params) req.send_request() end |
#create_label_group(params = {}) ⇒ Types::CreateLabelGroupResponse
Creates a group of labels.
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# File 'gems/aws-sdk-lookoutequipment/lib/aws-sdk-lookoutequipment/client.rb', line 783 def create_label_group(params = {}, = {}) req = build_request(:create_label_group, params) req.send_request() end |
#create_model(params = {}) ⇒ Types::CreateModelResponse
Creates a machine learning model for data inference.
A machine-learning (ML) model is a mathematical model that finds patterns in your data. In Amazon Lookout for Equipment, the model learns the patterns of normal behavior and detects abnormal behavior that could be potential equipment failure (or maintenance events). The models are made by analyzing normal data and abnormalities in machine behavior that have already occurred.
Your model is trained using a portion of the data from your dataset and uses that data to learn patterns of normal behavior and abnormal patterns that lead to equipment failure. Another portion of the data is used to evaluate the model's accuracy.
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# File 'gems/aws-sdk-lookoutequipment/lib/aws-sdk-lookoutequipment/client.rb', line 926 def create_model(params = {}, = {}) req = build_request(:create_model, params) req.send_request() end |
#create_retraining_scheduler(params = {}) ⇒ Types::CreateRetrainingSchedulerResponse
Creates a retraining scheduler on the specified model.
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# File 'gems/aws-sdk-lookoutequipment/lib/aws-sdk-lookoutequipment/client.rb', line 1039 def create_retraining_scheduler(params = {}, = {}) req = build_request(:create_retraining_scheduler, params) req.send_request() end |
#delete_dataset(params = {}) ⇒ Struct
Deletes a dataset and associated artifacts. The operation will check to see if any inference scheduler or data ingestion job is currently using the dataset, and if there isn't, the dataset, its metadata, and any associated data stored in S3 will be deleted. This does not affect any models that used this dataset for training and evaluation, but does prevent it from being used in the future.
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# File 'gems/aws-sdk-lookoutequipment/lib/aws-sdk-lookoutequipment/client.rb', line 1066 def delete_dataset(params = {}, = {}) req = build_request(:delete_dataset, params) req.send_request() end |
#delete_inference_scheduler(params = {}) ⇒ Struct
Deletes an inference scheduler that has been set up. Prior inference results will not be deleted.
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# File 'gems/aws-sdk-lookoutequipment/lib/aws-sdk-lookoutequipment/client.rb', line 1089 def delete_inference_scheduler(params = {}, = {}) req = build_request(:delete_inference_scheduler, params) req.send_request() end |
#delete_label(params = {}) ⇒ Struct
Deletes a label.
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# File 'gems/aws-sdk-lookoutequipment/lib/aws-sdk-lookoutequipment/client.rb', line 1117 def delete_label(params = {}, = {}) req = build_request(:delete_label, params) req.send_request() end |
#delete_label_group(params = {}) ⇒ Struct
Deletes a group of labels.
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# File 'gems/aws-sdk-lookoutequipment/lib/aws-sdk-lookoutequipment/client.rb', line 1141 def delete_label_group(params = {}, = {}) req = build_request(:delete_label_group, params) req.send_request() end |
#delete_model(params = {}) ⇒ Struct
Deletes a machine learning model currently available for Amazon Lookout for Equipment. This will prevent it from being used with an inference scheduler, even one that is already set up.
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# File 'gems/aws-sdk-lookoutequipment/lib/aws-sdk-lookoutequipment/client.rb', line 1165 def delete_model(params = {}, = {}) req = build_request(:delete_model, params) req.send_request() end |
#delete_resource_policy(params = {}) ⇒ Struct
Deletes the resource policy attached to the resource.
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# File 'gems/aws-sdk-lookoutequipment/lib/aws-sdk-lookoutequipment/client.rb', line 1188 def delete_resource_policy(params = {}, = {}) req = build_request(:delete_resource_policy, params) req.send_request() end |
#delete_retraining_scheduler(params = {}) ⇒ Struct
Deletes a retraining scheduler from a model. The retraining scheduler
must be in the STOPPED
status.
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# File 'gems/aws-sdk-lookoutequipment/lib/aws-sdk-lookoutequipment/client.rb', line 1218 def delete_retraining_scheduler(params = {}, = {}) req = build_request(:delete_retraining_scheduler, params) req.send_request() end |
#describe_data_ingestion_job(params = {}) ⇒ Types::DescribeDataIngestionJobResponse
Provides information on a specific data ingestion job such as creation time, dataset ARN, and status.
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# File 'gems/aws-sdk-lookoutequipment/lib/aws-sdk-lookoutequipment/client.rb', line 1286 def describe_data_ingestion_job(params = {}, = {}) req = build_request(:describe_data_ingestion_job, params) req.send_request() end |
#describe_dataset(params = {}) ⇒ Types::DescribeDatasetResponse
Provides a JSON description of the data in each time series dataset, including names, column names, and data types.
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# File 'gems/aws-sdk-lookoutequipment/lib/aws-sdk-lookoutequipment/client.rb', line 1354 def describe_dataset(params = {}, = {}) req = build_request(:describe_dataset, params) req.send_request() end |
#describe_inference_scheduler(params = {}) ⇒ Types::DescribeInferenceSchedulerResponse
Specifies information about the inference scheduler being used, including name, model, status, and associated metadata
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# File 'gems/aws-sdk-lookoutequipment/lib/aws-sdk-lookoutequipment/client.rb', line 1415 def describe_inference_scheduler(params = {}, = {}) req = build_request(:describe_inference_scheduler, params) req.send_request() end |
#describe_label(params = {}) ⇒ Types::DescribeLabelResponse
Returns the name of the label.
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# File 'gems/aws-sdk-lookoutequipment/lib/aws-sdk-lookoutequipment/client.rb', line 1465 def describe_label(params = {}, = {}) req = build_request(:describe_label, params) req.send_request() end |
#describe_label_group(params = {}) ⇒ Types::DescribeLabelGroupResponse
Returns information about the label group.
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# File 'gems/aws-sdk-lookoutequipment/lib/aws-sdk-lookoutequipment/client.rb', line 1502 def describe_label_group(params = {}, = {}) req = build_request(:describe_label_group, params) req.send_request() end |
#describe_model(params = {}) ⇒ Types::DescribeModelResponse
Provides a JSON containing the overall information about a specific machine learning model, including model name and ARN, dataset, training and evaluation information, status, and so on.
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# File 'gems/aws-sdk-lookoutequipment/lib/aws-sdk-lookoutequipment/client.rb', line 1618 def describe_model(params = {}, = {}) req = build_request(:describe_model, params) req.send_request() end |
#describe_model_version(params = {}) ⇒ Types::DescribeModelVersionResponse
Retrieves information about a specific machine learning model version.
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# File 'gems/aws-sdk-lookoutequipment/lib/aws-sdk-lookoutequipment/client.rb', line 1723 def describe_model_version(params = {}, = {}) req = build_request(:describe_model_version, params) req.send_request() end |
#describe_resource_policy(params = {}) ⇒ Types::DescribeResourcePolicyResponse
Provides the details of a resource policy attached to a resource.
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# File 'gems/aws-sdk-lookoutequipment/lib/aws-sdk-lookoutequipment/client.rb', line 1758 def describe_resource_policy(params = {}, = {}) req = build_request(:describe_resource_policy, params) req.send_request() end |
#describe_retraining_scheduler(params = {}) ⇒ Types::DescribeRetrainingSchedulerResponse
Provides a description of the retraining scheduler, including information such as the model name and retraining parameters.
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# File 'gems/aws-sdk-lookoutequipment/lib/aws-sdk-lookoutequipment/client.rb', line 1823 def describe_retraining_scheduler(params = {}, = {}) req = build_request(:describe_retraining_scheduler, params) req.send_request() end |
#import_dataset(params = {}) ⇒ Types::ImportDatasetResponse
Imports a dataset.
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# File 'gems/aws-sdk-lookoutequipment/lib/aws-sdk-lookoutequipment/client.rb', line 1886 def import_dataset(params = {}, = {}) req = build_request(:import_dataset, params) req.send_request() end |
#import_model_version(params = {}) ⇒ Types::ImportModelVersionResponse
Imports a model that has been trained successfully.
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# File 'gems/aws-sdk-lookoutequipment/lib/aws-sdk-lookoutequipment/client.rb', line 1984 def import_model_version(params = {}, = {}) req = build_request(:import_model_version, params) req.send_request() end |
#list_data_ingestion_jobs(params = {}) ⇒ Types::ListDataIngestionJobsResponse
Provides a list of all data ingestion jobs, including dataset name and ARN, S3 location of the input data, status, and so on.
The returned response is a pageable response and is Enumerable. For details on usage see PageableResponse.
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# File 'gems/aws-sdk-lookoutequipment/lib/aws-sdk-lookoutequipment/client.rb', line 2037 def list_data_ingestion_jobs(params = {}, = {}) req = build_request(:list_data_ingestion_jobs, params) req.send_request() end |
#list_datasets(params = {}) ⇒ Types::ListDatasetsResponse
Lists all datasets currently available in your account, filtering on the dataset name.
The returned response is a pageable response and is Enumerable. For details on usage see PageableResponse.
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# File 'gems/aws-sdk-lookoutequipment/lib/aws-sdk-lookoutequipment/client.rb', line 2083 def list_datasets(params = {}, = {}) req = build_request(:list_datasets, params) req.send_request() end |
#list_inference_events(params = {}) ⇒ Types::ListInferenceEventsResponse
Lists all inference events that have been found for the specified inference scheduler.
The returned response is a pageable response and is Enumerable. For details on usage see PageableResponse.
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# File 'gems/aws-sdk-lookoutequipment/lib/aws-sdk-lookoutequipment/client.rb', line 2141 def list_inference_events(params = {}, = {}) req = build_request(:list_inference_events, params) req.send_request() end |
#list_inference_executions(params = {}) ⇒ Types::ListInferenceExecutionsResponse
Lists all inference executions that have been performed by the specified inference scheduler.
The returned response is a pageable response and is Enumerable. For details on usage see PageableResponse.
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# File 'gems/aws-sdk-lookoutequipment/lib/aws-sdk-lookoutequipment/client.rb', line 2219 def list_inference_executions(params = {}, = {}) req = build_request(:list_inference_executions, params) req.send_request() end |
#list_inference_schedulers(params = {}) ⇒ Types::ListInferenceSchedulersResponse
Retrieves a list of all inference schedulers currently available for your account.
The returned response is a pageable response and is Enumerable. For details on usage see PageableResponse.
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# File 'gems/aws-sdk-lookoutequipment/lib/aws-sdk-lookoutequipment/client.rb', line 2278 def list_inference_schedulers(params = {}, = {}) req = build_request(:list_inference_schedulers, params) req.send_request() end |
#list_label_groups(params = {}) ⇒ Types::ListLabelGroupsResponse
Returns a list of the label groups.
The returned response is a pageable response and is Enumerable. For details on usage see PageableResponse.
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# File 'gems/aws-sdk-lookoutequipment/lib/aws-sdk-lookoutequipment/client.rb', line 2323 def list_label_groups(params = {}, = {}) req = build_request(:list_label_groups, params) req.send_request() end |
#list_labels(params = {}) ⇒ Types::ListLabelsResponse
Provides a list of labels.
The returned response is a pageable response and is Enumerable. For details on usage see PageableResponse.
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# File 'gems/aws-sdk-lookoutequipment/lib/aws-sdk-lookoutequipment/client.rb', line 2390 def list_labels(params = {}, = {}) req = build_request(:list_labels, params) req.send_request() end |
#list_model_versions(params = {}) ⇒ Types::ListModelVersionsResponse
Generates a list of all model versions for a given model, including
the model version, model version ARN, and status. To list a subset of
versions, use the MaxModelVersion
and MinModelVersion
fields.
The returned response is a pageable response and is Enumerable. For details on usage see PageableResponse.
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# File 'gems/aws-sdk-lookoutequipment/lib/aws-sdk-lookoutequipment/client.rb', line 2472 def list_model_versions(params = {}, = {}) req = build_request(:list_model_versions, params) req.send_request() end |
#list_models(params = {}) ⇒ Types::ListModelsResponse
Generates a list of all models in the account, including model name and ARN, dataset, and status.
The returned response is a pageable response and is Enumerable. For details on usage see PageableResponse.
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# File 'gems/aws-sdk-lookoutequipment/lib/aws-sdk-lookoutequipment/client.rb', line 2540 def list_models(params = {}, = {}) req = build_request(:list_models, params) req.send_request() end |
#list_retraining_schedulers(params = {}) ⇒ Types::ListRetrainingSchedulersResponse
Lists all retraining schedulers in your account, filtering by model name prefix and status.
The returned response is a pageable response and is Enumerable. For details on usage see PageableResponse.
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# File 'gems/aws-sdk-lookoutequipment/lib/aws-sdk-lookoutequipment/client.rb', line 2632 def list_retraining_schedulers(params = {}, = {}) req = build_request(:list_retraining_schedulers, params) req.send_request() end |
#list_sensor_statistics(params = {}) ⇒ Types::ListSensorStatisticsResponse
Lists statistics about the data collected for each of the sensors that have been successfully ingested in the particular dataset. Can also be used to retreive Sensor Statistics for a previous ingestion job.
The returned response is a pageable response and is Enumerable. For details on usage see PageableResponse.
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# File 'gems/aws-sdk-lookoutequipment/lib/aws-sdk-lookoutequipment/client.rb', line 2703 def list_sensor_statistics(params = {}, = {}) req = build_request(:list_sensor_statistics, params) req.send_request() end |
#list_tags_for_resource(params = {}) ⇒ Types::ListTagsForResourceResponse
Lists all the tags for a specified resource, including key and value.
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# File 'gems/aws-sdk-lookoutequipment/lib/aws-sdk-lookoutequipment/client.rb', line 2734 def (params = {}, = {}) req = build_request(:list_tags_for_resource, params) req.send_request() end |
#put_resource_policy(params = {}) ⇒ Types::PutResourcePolicyResponse
Creates a resource control policy for a given resource.
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# File 'gems/aws-sdk-lookoutequipment/lib/aws-sdk-lookoutequipment/client.rb', line 2781 def put_resource_policy(params = {}, = {}) req = build_request(:put_resource_policy, params) req.send_request() end |
#start_data_ingestion_job(params = {}) ⇒ Types::StartDataIngestionJobResponse
Starts a data ingestion job. Amazon Lookout for Equipment returns the job status.
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# File 'gems/aws-sdk-lookoutequipment/lib/aws-sdk-lookoutequipment/client.rb', line 2836 def start_data_ingestion_job(params = {}, = {}) req = build_request(:start_data_ingestion_job, params) req.send_request() end |
#start_inference_scheduler(params = {}) ⇒ Types::StartInferenceSchedulerResponse
Starts an inference scheduler.
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# File 'gems/aws-sdk-lookoutequipment/lib/aws-sdk-lookoutequipment/client.rb', line 2872 def start_inference_scheduler(params = {}, = {}) req = build_request(:start_inference_scheduler, params) req.send_request() end |
#start_retraining_scheduler(params = {}) ⇒ Types::StartRetrainingSchedulerResponse
Starts a retraining scheduler.
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# File 'gems/aws-sdk-lookoutequipment/lib/aws-sdk-lookoutequipment/client.rb', line 2918 def start_retraining_scheduler(params = {}, = {}) req = build_request(:start_retraining_scheduler, params) req.send_request() end |
#stop_inference_scheduler(params = {}) ⇒ Types::StopInferenceSchedulerResponse
Stops an inference scheduler.
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# File 'gems/aws-sdk-lookoutequipment/lib/aws-sdk-lookoutequipment/client.rb', line 2954 def stop_inference_scheduler(params = {}, = {}) req = build_request(:stop_inference_scheduler, params) req.send_request() end |
#stop_retraining_scheduler(params = {}) ⇒ Types::StopRetrainingSchedulerResponse
Stops a retraining scheduler.
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# File 'gems/aws-sdk-lookoutequipment/lib/aws-sdk-lookoutequipment/client.rb', line 3000 def stop_retraining_scheduler(params = {}, = {}) req = build_request(:stop_retraining_scheduler, params) req.send_request() end |
#tag_resource(params = {}) ⇒ Struct
Associates a given tag to a resource in your account. A tag is a key-value pair which can be added to an Amazon Lookout for Equipment resource as metadata. Tags can be used for organizing your resources as well as helping you to search and filter by tag. Multiple tags can be added to a resource, either when you create it, or later. Up to 50 tags can be associated with each resource.
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# File 'gems/aws-sdk-lookoutequipment/lib/aws-sdk-lookoutequipment/client.rb', line 3038 def tag_resource(params = {}, = {}) req = build_request(:tag_resource, params) req.send_request() end |
#untag_resource(params = {}) ⇒ Struct
Removes a specific tag from a given resource. The tag is specified by its key.
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# File 'gems/aws-sdk-lookoutequipment/lib/aws-sdk-lookoutequipment/client.rb', line 3066 def untag_resource(params = {}, = {}) req = build_request(:untag_resource, params) req.send_request() end |
#update_active_model_version(params = {}) ⇒ Types::UpdateActiveModelVersionResponse
Sets the active model version for a given machine learning model.
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# File 'gems/aws-sdk-lookoutequipment/lib/aws-sdk-lookoutequipment/client.rb', line 3110 def update_active_model_version(params = {}, = {}) req = build_request(:update_active_model_version, params) req.send_request() end |
#update_inference_scheduler(params = {}) ⇒ Struct
Updates an inference scheduler.
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# File 'gems/aws-sdk-lookoutequipment/lib/aws-sdk-lookoutequipment/client.rb', line 3185 def update_inference_scheduler(params = {}, = {}) req = build_request(:update_inference_scheduler, params) req.send_request() end |
#update_label_group(params = {}) ⇒ Struct
Updates the label group.
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# File 'gems/aws-sdk-lookoutequipment/lib/aws-sdk-lookoutequipment/client.rb', line 3215 def update_label_group(params = {}, = {}) req = build_request(:update_label_group, params) req.send_request() end |
#update_model(params = {}) ⇒ Struct
Updates a model in the account.
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# File 'gems/aws-sdk-lookoutequipment/lib/aws-sdk-lookoutequipment/client.rb', line 3274 def update_model(params = {}, = {}) req = build_request(:update_model, params) req.send_request() end |
#update_retraining_scheduler(params = {}) ⇒ Struct
Updates a retraining scheduler.
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# File 'gems/aws-sdk-lookoutequipment/lib/aws-sdk-lookoutequipment/client.rb', line 3343 def update_retraining_scheduler(params = {}, = {}) req = build_request(:update_retraining_scheduler, params) req.send_request() end |