@Generated(value="software.amazon.awssdk:codegen") public class GetMLModelResponse extends MachineLearningResponse implements ToCopyableBuilder<GetMLModelResponse.Builder,GetMLModelResponse>
Represents the output of a GetMLModel
operation, and provides detailed information about a
MLModel
.
Modifier and Type | Class and Description |
---|---|
static interface |
GetMLModelResponse.Builder |
Modifier and Type | Method and Description |
---|---|
static GetMLModelResponse.Builder |
builder() |
Long |
computeTime()
The approximate CPU time in milliseconds that Amazon Machine Learning spent processing the
MLModel ,
normalized and scaled on computation resources. |
Instant |
createdAt()
The time that the
MLModel was created. |
String |
createdByIamUser()
The AWS user account from which the
MLModel was created. |
RealtimeEndpointInfo |
endpointInfo()
The current endpoint of the
MLModel |
boolean |
equals(Object obj) |
Instant |
finishedAt()
The epoch time when Amazon Machine Learning marked the
MLModel as COMPLETED or
FAILED . |
<T> Optional<T> |
getValueForField(String fieldName,
Class<T> clazz)
Used to retrieve the value of a field from any class that extends
SdkResponse . |
int |
hashCode() |
String |
inputDataLocationS3()
The location of the data file or directory in Amazon Simple Storage Service (Amazon S3).
|
Instant |
lastUpdatedAt()
The time of the most recent edit to the
MLModel . |
String |
logUri()
A link to the file that contains logs of the
CreateMLModel operation. |
String |
message()
A description of the most recent details about accessing the
MLModel . |
String |
mlModelId()
The MLModel ID, which is
same as the
MLModelId in the request. |
MLModelType |
mlModelType()
Identifies the
MLModel category. |
String |
mlModelTypeString()
Identifies the
MLModel category. |
String |
name()
A user-supplied name or description of the
MLModel . |
String |
recipe()
The recipe to use when training the
MLModel . |
String |
schema()
The schema used by all of the data files referenced by the
DataSource . |
Float |
scoreThreshold()
The scoring threshold is used in binary classification
MLModel models. |
Instant |
scoreThresholdLastUpdatedAt()
The time of the most recent edit to the
ScoreThreshold . |
static Class<? extends GetMLModelResponse.Builder> |
serializableBuilderClass() |
Long |
sizeInBytes()
Returns the value of the SizeInBytes property for this object.
|
Instant |
startedAt()
The epoch time when Amazon Machine Learning marked the
MLModel as INPROGRESS . |
EntityStatus |
status()
The current status of the
MLModel . |
String |
statusString()
The current status of the
MLModel . |
GetMLModelResponse.Builder |
toBuilder()
Take this object and create a builder that contains all of the current property values of this object.
|
String |
toString() |
String |
trainingDataSourceId()
The ID of the training
DataSource . |
Map<String,String> |
trainingParameters()
A list of the training parameters in the
MLModel . |
copy
public String mlModelId()
The MLModel ID, which is
same as the MLModelId
in the request.
MLModelId
in the request.public String trainingDataSourceId()
The ID of the training DataSource
.
DataSource
.public String createdByIamUser()
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.
MLModel
was created. The account type can be either an
AWS root account or an AWS Identity and Access Management (IAM) user account.public Instant createdAt()
The time that the MLModel
was created. The time is expressed in epoch time.
MLModel
was created. The time is expressed in epoch time.public Instant lastUpdatedAt()
The time of the most recent edit to the MLModel
. The time is expressed in epoch time.
MLModel
. The time is expressed in epoch time.public String name()
A user-supplied name or description of the MLModel
.
MLModel
.public EntityStatus status()
The current status of the 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. The ML model isn't usable.COMPLETED
- The request completed successfully.DELETED
- The MLModel
is marked as deleted. It isn't usable.
If the service returns an enum value that is not available in the current SDK version, status
will
return EntityStatus.UNKNOWN_TO_SDK_VERSION
. The raw value returned by the service is available from
statusString()
.
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. The ML model isn't usable.COMPLETED
- The request completed successfully.DELETED
- The MLModel
is marked as deleted. It isn't usable.EntityStatus
public String statusString()
The current status of the 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. The ML model isn't usable.COMPLETED
- The request completed successfully.DELETED
- The MLModel
is marked as deleted. It isn't usable.
If the service returns an enum value that is not available in the current SDK version, status
will
return EntityStatus.UNKNOWN_TO_SDK_VERSION
. The raw value returned by the service is available from
statusString()
.
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. The ML model isn't usable.COMPLETED
- The request completed successfully.DELETED
- The MLModel
is marked as deleted. It isn't usable.EntityStatus
public Long sizeInBytes()
public RealtimeEndpointInfo endpointInfo()
The current endpoint of the MLModel
MLModel
public Map<String,String> trainingParameters()
A list of the training parameters in the MLModel
. The list is implemented as a map of key-value
pairs.
The following is the current set of training parameters:
sgd.maxMLModelSizeInBytes
- The maximum allowed size of the model. Depending on the input data, the
size of the model might affect its performance.
The value is an integer that ranges from 100000
to 2147483648
. The default value is
33554432
.
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.shuffleType
- Whether Amazon ML shuffles the training data. Shuffling data improves a model's
ability to find the optimal solution for a variety of data types. The valid values are auto
and
none
. The default value is none
. We strongly recommend that you shuffle your data.
sgd.l1RegularizationAmount
- The 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, start by specifying a small value, such as 1.0E-08
.
The value is a double that ranges from 0
to MAX_DOUBLE
. The default is to not use L1
normalization. This parameter can't be used when L2
is specified. Use this parameter sparingly.
sgd.l2RegularizationAmount
- The 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, start by specifying a small value, such as 1.0E-08
.
The value is a double that ranges from 0
to MAX_DOUBLE
. The default is to not use L2
normalization. This parameter can't be used when L1
is specified. Use this parameter sparingly.
Attempts to modify the collection returned by this method will result in an UnsupportedOperationException.
MLModel
. The list is implemented as a map of
key-value pairs.
The following is the current set of training parameters:
sgd.maxMLModelSizeInBytes
- The maximum allowed size of the model. Depending on the input
data, the size of the model might affect its performance.
The value is an integer that ranges from 100000
to 2147483648
. The default
value is 33554432
.
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.shuffleType
- Whether Amazon ML shuffles the training data. Shuffling data improves a
model's ability to find the optimal solution for a variety of data types. The valid values are
auto
and none
. The default value is none
. We strongly recommend
that you shuffle your data.
sgd.l1RegularizationAmount
- The 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, start by specifying a small value, such as
1.0E-08
.
The value is a double that ranges from 0
to MAX_DOUBLE
. The default is to not
use L1 normalization. This parameter can't be used when L2
is specified. Use this parameter
sparingly.
sgd.l2RegularizationAmount
- The 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, start by specifying a small value, such as 1.0E-08
.
The value is a double that ranges from 0
to MAX_DOUBLE
. The default is to not
use L2 normalization. This parameter can't be used when L1
is specified. Use this parameter
sparingly.
public String inputDataLocationS3()
The location of the data file or directory in Amazon Simple Storage Service (Amazon S3).
public MLModelType mlModelType()
Identifies the MLModel
category. The following are the available types:
If the service returns an enum value that is not available in the current SDK version, mlModelType
will
return MLModelType.UNKNOWN_TO_SDK_VERSION
. The raw value returned by the service is available from
mlModelTypeString()
.
MLModel
category. The following are the available types:
MLModelType
public String mlModelTypeString()
Identifies the MLModel
category. The following are the available types:
If the service returns an enum value that is not available in the current SDK version, mlModelType
will
return MLModelType.UNKNOWN_TO_SDK_VERSION
. The raw value returned by the service is available from
mlModelTypeString()
.
MLModel
category. The following are the available types:
MLModelType
public Float scoreThreshold()
The scoring threshold is used in binary classification MLModel
models. It 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
.
MLModel
models. It 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
.
public Instant scoreThresholdLastUpdatedAt()
The time of the most recent edit to the ScoreThreshold
. The time is expressed in epoch time.
ScoreThreshold
. The time is expressed in epoch time.public String logUri()
A link to the file that contains logs of the CreateMLModel
operation.
CreateMLModel
operation.public String message()
A description of the most recent details about accessing the MLModel
.
MLModel
.public Long computeTime()
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.
MLModel
, normalized and scaled on computation resources. ComputeTime
is only
available if the MLModel
is in the COMPLETED
state.public Instant finishedAt()
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.
MLModel
as COMPLETED
or
FAILED
. FinishedAt
is only available when the MLModel
is in the
COMPLETED
or FAILED
state.public Instant startedAt()
The epoch time when Amazon Machine Learning marked the MLModel
as INPROGRESS
.
StartedAt
isn't available if the MLModel
is in the PENDING
state.
MLModel
as INPROGRESS
.
StartedAt
isn't available if the MLModel
is in the PENDING
state.public String recipe()
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.
This parameter is provided as part of the verbose format.
MLModel
. The Recipe
provides detailed
information about the observation data to use during training, and manipulations to perform on the
observation data during training. This parameter is provided as part of the verbose format.
public String schema()
The schema used by all of the data files referenced by the DataSource
.
This parameter is provided as part of the verbose format.
DataSource
.
This parameter is provided as part of the verbose format.
public GetMLModelResponse.Builder toBuilder()
ToCopyableBuilder
toBuilder
in interface ToCopyableBuilder<GetMLModelResponse.Builder,GetMLModelResponse>
toBuilder
in class AwsResponse
public static GetMLModelResponse.Builder builder()
public static Class<? extends GetMLModelResponse.Builder> serializableBuilderClass()
public <T> Optional<T> getValueForField(String fieldName, Class<T> clazz)
SdkResponse
SdkResponse
. The field name
specified should match the member name from the corresponding service-2.json model specified in the
codegen-resources folder for a given service. The class specifies what class to cast the returned value to.
If the returned value is also a modeled class, the SdkResponse.getValueForField(String, Class)
method will
again be available.getValueForField
in class SdkResponse
fieldName
- The name of the member to be retrieved.clazz
- The class to cast the returned object to.Copyright © 2017 Amazon Web Services, Inc. All Rights Reserved.