Entity that comprises information on categorical values in data.

Entity that comprises information of count and percentage.

Provides information about a specified data ingestion job, including dataset information, data ingestion configuration, and status.

The configuration is the TargetSamplingRate, which is the sampling rate of the data after post processing by Amazon Lookout for Equipment. For example, if you provide data that has been collected at a 1 second level and you want the system to resample the data at a 1 minute rate before training, the TargetSamplingRate is 1 minute.

DataQualitySummary gives aggregated statistics over all the sensors about a completed ingestion job. It primarily gives more information about statistics over different incorrect data like MissingCompleteSensorData, MissingSensorData, UnsupportedDateFormats, InsufficientSensorData, DuplicateTimeStamps.

Provides information about the data schema used with the given dataset.

Contains information about the specific data set, including name, ARN, and status.

Entity that comprises information abount duplicate timestamps in the dataset.

Contains information about the specific inference event, including start and end time, diagnostics information, event duration and so on.

Contains information about the specific inference execution, including input and output data configuration, inference scheduling information, status, and so on.

Specifies configuration information for the input data for the inference, including Amazon S3 location of input data..

Specifies configuration information for the input data for the inference, including timestamp format and delimiter.

Specifies configuration information for the output results from for the inference, including KMS key ID and output S3 location.

Specifies configuration information for the input data for the inference, including input data S3 location.

Specifies configuration information for the output results from the inference, including output S3 location.

Contains information about the specific inference scheduler, including data delay offset, model name and ARN, status, and so on.

Gives statistics about how many files have been ingested, and which files have not been ingested, for a particular ingestion job.

Specifies configuration information for the input data for the data ingestion job, including input data S3 location.

Specifies S3 configuration information for the input data for the data ingestion job.

Entity that comprises aggregated information on sensors having insufficient data.

Entity that comprises aggregated information on sensors having insufficient data.

Contains information about the label group.

Contains the configuration information for the S3 location being used to hold label data.

The location information (prefix and bucket name) for the s3 location being used for label data.

Information about the label.

Entity that comprises information on large gaps between consecutive timestamps in data.

Entity that comprises information on sensors that have sensor data completely missing.

Entity that comprises aggregated information on sensors having missing data.

Output configuration information for the pointwise model diagnostics for an Amazon Lookout for Equipment model.

The Amazon S3 location for the pointwise model diagnostics for an Amazon Lookout for Equipment model.

Provides information about the specified machine learning model, including dataset and model names and ARNs, as well as status.

Contains information about the specific model version.

Entity that comprises information on monotonic values in the data.

Entity that comprises information on operating modes in data.

Provides information about the specified retraining scheduler, including model name, status, start date, frequency, and lookback window.

Contains information about an S3 bucket.

Summary of ingestion statistics like whether data exists, number of missing values, number of invalid values and so on related to the particular sensor.

Entity that comprises information on sensors that have shorter date range.

A tag is a key-value pair that can be added to a resource as metadata.

Entity that comprises information abount unsupported timestamps in the dataset.