{ "uuid": "d88012f7-0272-4f2b-889a-9cb2228c2d10", "lastMigration": 29, "name": "Amazon Lookout for Equipment", "endpointPrefix": "", "latency": 0, "port": 3000, "hostname": "", "routes": [ { "uuid": "b8606920-bcfc-40ae-a474-86a7889baba5", "documentation": "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. 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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.

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", "method": "post", "endpoint": "#X-Amz-Target=AWSLookoutEquipmentFrontendService.DeleteDataset", "responses": [ { "uuid": "0c52abf9-1236-4678-8fbd-1ff510ca9ce3", "body": "", "latency": 0, "statusCode": 200, "label": "Success", "headers": [{ "key": "Content-Type", "value": "application/json" }], "bodyType": "INLINE", "filePath": "", "databucketID": "", "sendFileAsBody": false, "rules": [], "rulesOperator": "OR", "disableTemplating": false, "fallbackTo404": false, "default": true, "crudKey": "id" }, { "uuid": "db0d32fe-66c2-4ff0-bc16-aec11f1ca749", "body": "\"\"", "latency": 0, "statusCode": 480, "label": "ResourceNotFoundException", "headers": [{ "key": "Content-Type", "value": "application/json" }], "bodyType": "INLINE", "filePath": "", "databucketID": "", "sendFileAsBody": false, "rules": [], "rulesOperator": "OR", "disableTemplating": false, "fallbackTo404": false, "default": false, "crudKey": "id" }, { "uuid": "5d4052fa-ef66-4aa5-9554-4341a24fc9a4", "body": "\"\"", "latency": 0, "statusCode": 481, "label": "ThrottlingException", "headers": [{ "key": "Content-Type", "value": "application/json" }], "bodyType": "INLINE", "filePath": "", "databucketID": "", "sendFileAsBody": false, "rules": [], "rulesOperator": "OR", "disableTemplating": false, "fallbackTo404": false, "default": false, "crudKey": "id" }, { "uuid": "af6c94da-4116-430d-ad5b-251c5370d0b3", "body": "\"\"", "latency": 0, "statusCode": 482, "label": "InternalServerException", "headers": [{ "key": "Content-Type", "value": "application/json" }], "bodyType": "INLINE", "filePath": "", "databucketID": "", "sendFileAsBody": false, "rules": [], "rulesOperator": "OR", "disableTemplating": false, "fallbackTo404": false, "default": false, "crudKey": "id" }, { "uuid": "ee77ed07-8587-49b8-827a-3d006150eb21", "body": "\"\"", "latency": 0, "statusCode": 483, "label": "AccessDeniedException", "headers": [{ "key": "Content-Type", "value": "application/json" }], "bodyType": "INLINE", "filePath": "", "databucketID": "", "sendFileAsBody": false, "rules": [], "rulesOperator": "OR", "disableTemplating": false, "fallbackTo404": false, "default": false, "crudKey": "id" }, { "uuid": "16c6f056-87de-4ad4-a1c1-9977bb6d0171", "body": "\"\"", "latency": 0, "statusCode": 484, "label": "ConflictException", "headers": [{ "key": "Content-Type", "value": "application/json" }], "bodyType": "INLINE", "filePath": "", "databucketID": "", "sendFileAsBody": false, "rules": [], "rulesOperator": "OR", "disableTemplating": false, "fallbackTo404": false, "default": false, "crudKey": "id" } ], "enabled": true, "responseMode": null, "type": "http" }, { "uuid": "f00e787a-2623-4d7c-99f0-ff160f452ee5", "documentation": "Deletes an inference scheduler that has been set up. 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