String mLModelId
MLModelId
in the
request.
Constraints:
Length: 1 - 64
Pattern: [a-zA-Z0-9_.-]+
String trainingDataSourceId
DataSource
.
Constraints:
Length: 1 - 64
Pattern: [a-zA-Z0-9_.-]+
String createdByIamUser
MLModel
was created.
The account type can be either an AWS root account or an AWS Identity
and Access Management (IAM) user account.
Constraints:
Pattern: arn:aws:iam::[0-9]+:((user/.+)|(root))
Date createdAt
MLModel
was created. The time is
expressed in epoch time.Date lastUpdatedAt
MLModel
. The time
is expressed in epoch time.String name
MLModel
.
Constraints:
Length: 0 - 1024
String status
MLModel
. This element can have
one of the following values: PENDING
- Amazon
Machine Learning (Amazon ML) submitted a request to describe a
MLModel
.INPROGRESS
- The request
is processing.FAILED
- The request did not run
to completion. It is not usable.COMPLETED
- The
request completed successfully.DELETED
- The
MLModel
is marked as deleted. It is not usable.
Constraints:
Allowed Values: PENDING, INPROGRESS, FAILED, COMPLETED, DELETED
Long sizeInBytes
RealtimeEndpointInfo endpointInfo
MLModel
Map<K,V> trainingParameters
MLModel
. The
list is implemented as a map of key/value pairs. The following is the current set of training parameters:
sgd.l1RegularizationAmount
- Coefficient
regularization L1 norm. It controls overfitting the data by penalizing
large coefficients. This tends to drive coefficients to zero,
resulting in a sparse feature set. If you use this parameter, specify
a small value, such as 1.0E-04 or 1.0E-08.
The value is a double
that ranges from 0 to MAX_DOUBLE. The default is not to use L1
normalization. The parameter cannot be used when L2
is
specified. Use this parameter sparingly.
sgd.l2RegularizationAmount
- Coefficient
regularization L2 norm. It controls overfitting the data by penalizing
large coefficients. This tends to drive coefficients to small, nonzero
values. If you use this parameter, specify a small value, such as
1.0E-04 or 1.0E-08.
The value is a double that ranges from 0 to
MAX_DOUBLE. The default is not to use L2 normalization. This parameter
cannot be used when L1
is specified. Use this parameter
sparingly.
sgd.maxPasses
- The number of
times that the training process traverses the observations to build
the MLModel
. The value is an integer that ranges from 1
to 10000. The default value is 10.
sgd.maxMLModelSizeInBytes
- The maximum allowed
size of the model. Depending on the input data, the model size might
affect performance.
The value is an integer that ranges from 100000 to 2147483648. The default value is 33554432.
String inputDataLocationS3
Constraints:
Length: 0 - 2048
Pattern: s3://([^/]+)(/.*)?
String mLModelType
MLModel
category. The following are the
available types:
Constraints:
Allowed Values: REGRESSION, BINARY, MULTICLASS
Float scoreThreshold
MLModel
s, and marks the boundary between a positive
prediction and a negative prediction. Output values greater than or
equal to the threshold receive a positive result from the MLModel,
such as true
. Output values less than the threshold
receive a negative response from the MLModel, such as
false
.
Date scoreThresholdLastUpdatedAt
ScoreThreshold
.
The time is expressed in epoch time.String logUri
CreateMLModel
operation.String message
MLModel
.
Constraints:
Length: 0 - 10240
String recipe
MLModel
. The
Recipe
provides detailed information about the
observation data to use during training, as well as manipulations to
perform on the observation data during training.
This parameter is provided as part of the verbose format.
Constraints:
Length: 0 - 131071
String schema
DataSource
. This parameter is provided as part of the verbose format.
Constraints:
Length: 0 - 131071
Integer code
Integer code
Integer code
String predictedLabel
MLModel
.
Constraints:
Length: 1 -
Float predictedValue
MLModel
.Map<K,V> predictedScores
Map<K,V> details
Prediction prediction
Predict
operation:
Details
- Contains the following attributes:
DetailsAttributes.PREDICTIVE_MODEL_TYPE - REGRESSION | BINARY |
MULTICLASS DetailsAttributes.ALGORITHM - SGD
PredictedLabel
- Present for either a BINARY or
MULTICLASS MLModel
request.
PredictedScores
- Contains the raw classification score
corresponding to each label.
PredictedValue
- Present for a REGRESSION
MLModel
request.
Integer peakRequestsPerSecond
MLModel
, measured in incoming requests per second.Date createdAt
MLModel
was received. The time is expressed in epoch
time.String endpointUrl
MLModel
. The application must wait until the real-time endpoint is ready before using this URI.
Constraints:
Length: 0 - 2048
Pattern: https://[a-zA-Z0-9-.]*\.amazon(aws)?\.com[/]?
String endpointStatus
MLModel
. This element can have one of the following
values:
Constraints:
Allowed Values: NONE, READY, UPDATING, FAILED
Integer code
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