GetMlModelResponse

The approximate CPU time in milliseconds that Amazon Machine Learning spent processing the MLModel, normalized and scaled on computation resources. ComputeTime is only available if the MLModel is in the COMPLETED state.

The time that the MLModel was created. The time is expressed in epoch time.

The AWS user account from which the MLModel was created. The account type can be either an AWS root account or an AWS Identity and Access Management (IAM) user account.

The current endpoint of the MLModel

The epoch time when Amazon Machine Learning marked the MLModel as COMPLETED or FAILED. FinishedAt is only available when the MLModel is in the COMPLETED or FAILED state.

The location of the data file or directory in Amazon Simple Storage Service (Amazon S3).

The time of the most recent edit to the MLModel. The time is expressed in epoch time.

A link to the file that contains logs of the CreateMLModel operation.

A description of the most recent details about accessing the MLModel.

The MLModel ID, which is same as the MLModelId in the request.

Identifies the MLModel category. The following are the available types:

A user-supplied name or description of the MLModel.

The recipe to use when training the MLModel. The Recipe provides detailed information about the observation data to use during training, and manipulations to perform on the observation data during training.

The schema used by all of the data files referenced by the DataSource.

The scoring threshold is used in binary classification MLModel models. It marks the boundary between a positive prediction and a negative prediction.

The time of the most recent edit to the ScoreThreshold. The time is expressed in epoch time.

Long integer type that is a 64-bit signed number.

The epoch time when Amazon Machine Learning marked the MLModel as INPROGRESS. StartedAt isn't available if the MLModel is in the PENDING state.

The current status of the MLModel. This element can have one of the following values:

The ID of the training DataSource.

A list of the training parameters in the MLModel. The list is implemented as a map of key-value pairs.