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NAMEPaws::LookoutEquipment - Perl Interface to AWS Amazon Lookout for Equipment SYNOPSISuse Paws; my $obj = Paws->service('LookoutEquipment'); my $res = $obj->Method( Arg1 => $val1, Arg2 => [ 'V1', 'V2' ], # if Arg3 is an object, the HashRef will be used as arguments to the constructor # of the arguments type Arg3 => { Att1 => 'Val1' }, # if Arg4 is an array of objects, the HashRefs will be passed as arguments to # the constructor of the arguments type Arg4 => [ { Att1 => 'Val1' }, { Att1 => 'Val2' } ], ); DESCRIPTIONAmazon Lookout for Equipment is a machine learning service that uses advanced analytics to identify anomalies in machines from sensor data for use in predictive maintenance. For the AWS API documentation, see <https://docs.aws.amazon.com/goto/WebAPI/lookoutequipment-2020-12-15> METHODSCreateDataset
Each argument is described in detail in: Paws::LookoutEquipment::CreateDataset Returns: a Paws::LookoutEquipment::CreateDatasetResponse instance 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. In other words, 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. CreateInferenceScheduler
Each argument is described in detail in: Paws::LookoutEquipment::CreateInferenceScheduler Returns: a Paws::LookoutEquipment::CreateInferenceSchedulerResponse instance 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. CreateModel
Each argument is described in detail in: Paws::LookoutEquipment::CreateModel Returns: a Paws::LookoutEquipment::CreateModelResponse instance Creates an ML 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. DeleteDatasetEach argument is described in detail in: Paws::LookoutEquipment::DeleteDataset Returns: nothing 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. DeleteInferenceSchedulerEach argument is described in detail in: Paws::LookoutEquipment::DeleteInferenceScheduler Returns: nothing Deletes an inference scheduler that has been set up. Already processed output results are not affected. DeleteModelEach argument is described in detail in: Paws::LookoutEquipment::DeleteModel Returns: nothing Deletes an ML 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. DescribeDataIngestionJobEach argument is described in detail in: Paws::LookoutEquipment::DescribeDataIngestionJob Returns: a Paws::LookoutEquipment::DescribeDataIngestionJobResponse instance Provides information on a specific data ingestion job such as creation time, dataset ARN, status, and so on. DescribeDatasetEach argument is described in detail in: Paws::LookoutEquipment::DescribeDataset Returns: a Paws::LookoutEquipment::DescribeDatasetResponse instance Provides information on a specified dataset such as the schema location, status, and so on. DescribeInferenceSchedulerEach argument is described in detail in: Paws::LookoutEquipment::DescribeInferenceScheduler Returns: a Paws::LookoutEquipment::DescribeInferenceSchedulerResponse instance Specifies information about the inference scheduler being used, including name, model, status, and associated metadata DescribeModelEach argument is described in detail in: Paws::LookoutEquipment::DescribeModel Returns: a Paws::LookoutEquipment::DescribeModelResponse instance Provides overall information about a specific ML model, including model name and ARN, dataset, training and evaluation information, status, and so on. ListDataIngestionJobs
Each argument is described in detail in: Paws::LookoutEquipment::ListDataIngestionJobs Returns: a Paws::LookoutEquipment::ListDataIngestionJobsResponse instance Provides a list of all data ingestion jobs, including dataset name and ARN, S3 location of the input data, status, and so on. ListDatasets
Each argument is described in detail in: Paws::LookoutEquipment::ListDatasets Returns: a Paws::LookoutEquipment::ListDatasetsResponse instance Lists all datasets currently available in your account, filtering on the dataset name. ListInferenceExecutions
Each argument is described in detail in: Paws::LookoutEquipment::ListInferenceExecutions Returns: a Paws::LookoutEquipment::ListInferenceExecutionsResponse instance Lists all inference executions that have been performed by the specified inference scheduler. ListInferenceSchedulers
Each argument is described in detail in: Paws::LookoutEquipment::ListInferenceSchedulers Returns: a Paws::LookoutEquipment::ListInferenceSchedulersResponse instance Retrieves a list of all inference schedulers currently available for your account. ListModels
Each argument is described in detail in: Paws::LookoutEquipment::ListModels Returns: a Paws::LookoutEquipment::ListModelsResponse instance Generates a list of all models in the account, including model name and ARN, dataset, and status. ListTagsForResourceEach argument is described in detail in: Paws::LookoutEquipment::ListTagsForResource Returns: a Paws::LookoutEquipment::ListTagsForResourceResponse instance Lists all the tags for a specified resource, including key and value. StartDataIngestionJob
Each argument is described in detail in: Paws::LookoutEquipment::StartDataIngestionJob Returns: a Paws::LookoutEquipment::StartDataIngestionJobResponse instance Starts a data ingestion job. Amazon Lookout for Equipment returns the job status. StartInferenceSchedulerEach argument is described in detail in: Paws::LookoutEquipment::StartInferenceScheduler Returns: a Paws::LookoutEquipment::StartInferenceSchedulerResponse instance Starts an inference scheduler. StopInferenceSchedulerEach argument is described in detail in: Paws::LookoutEquipment::StopInferenceScheduler Returns: a Paws::LookoutEquipment::StopInferenceSchedulerResponse instance Stops an inference scheduler. TagResourceEach argument is described in detail in: Paws::LookoutEquipment::TagResource Returns: a Paws::LookoutEquipment::TagResourceResponse instance 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. UntagResourceEach argument is described in detail in: Paws::LookoutEquipment::UntagResource Returns: a Paws::LookoutEquipment::UntagResourceResponse instance Removes a specific tag from a given resource. The tag is specified by its key. UpdateInferenceScheduler
Each argument is described in detail in: Paws::LookoutEquipment::UpdateInferenceScheduler Returns: nothing Updates an inference scheduler. PAGINATORSPaginator methods are helpers that repetively call methods that return partial results SEE ALSOThis service class forms part of Paws BUGS and CONTRIBUTIONSThe source code is located here: <https://github.com/pplu/aws-sdk-perl> Please report bugs to: <https://github.com/pplu/aws-sdk-perl/issues>
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