DescribeMLModels
Returns a list of MLModel
that match the search criteria in the request.
Request Syntax
{
"EQ": "string
",
"FilterVariable": "string
",
"GE": "string
",
"GT": "string
",
"LE": "string
",
"Limit": number
,
"LT": "string
",
"NE": "string
",
"NextToken": "string
",
"Prefix": "string
",
"SortOrder": "string
"
}
Request Parameters
For information about the parameters that are common to all actions, see Common Parameters.
The request accepts the following data in JSON format.
- EQ
-
The equal to operator. The
MLModel
results will haveFilterVariable
values that exactly match the value specified withEQ
.Type: String
Length Constraints: Maximum length of 1024.
Pattern:
.*\S.*|^$
Required: No
- FilterVariable
-
Use one of the following variables to filter a list of
MLModel
:-
CreatedAt
- Sets the search criteria toMLModel
creation date. -
Status
- Sets the search criteria toMLModel
status. -
Name
- Sets the search criteria to the contents ofMLModel
Name
. -
IAMUser
- Sets the search criteria to the user account that invoked theMLModel
creation. -
TrainingDataSourceId
- Sets the search criteria to theDataSource
used to train one or moreMLModel
. -
RealtimeEndpointStatus
- Sets the search criteria to theMLModel
real-time endpoint status. -
MLModelType
- Sets the search criteria toMLModel
type: binary, regression, or multi-class. -
Algorithm
- Sets the search criteria to the algorithm that theMLModel
uses. -
TrainingDataURI
- Sets the search criteria to the data file(s) used in training aMLModel
. The URL can identify either a file or an Amazon Simple Storage Service (Amazon S3) bucket or directory.
Type: String
Valid Values:
CreatedAt | LastUpdatedAt | Status | Name | IAMUser | TrainingDataSourceId | RealtimeEndpointStatus | MLModelType | Algorithm | TrainingDataURI
Required: No
-
- GE
-
The greater than or equal to operator. The
MLModel
results will haveFilterVariable
values that are greater than or equal to the value specified withGE
.Type: String
Length Constraints: Maximum length of 1024.
Pattern:
.*\S.*|^$
Required: No
- GT
-
The greater than operator. The
MLModel
results will haveFilterVariable
values that are greater than the value specified withGT
.Type: String
Length Constraints: Maximum length of 1024.
Pattern:
.*\S.*|^$
Required: No
- LE
-
The less than or equal to operator. The
MLModel
results will haveFilterVariable
values that are less than or equal to the value specified withLE
.Type: String
Length Constraints: Maximum length of 1024.
Pattern:
.*\S.*|^$
Required: No
- Limit
-
The number of pages of information to include in the result. The range of acceptable values is
1
through100
. The default value is100
.Type: Integer
Valid Range: Minimum value of 1. Maximum value of 100.
Required: No
- LT
-
The less than operator. The
MLModel
results will haveFilterVariable
values that are less than the value specified withLT
.Type: String
Length Constraints: Maximum length of 1024.
Pattern:
.*\S.*|^$
Required: No
- NE
-
The not equal to operator. The
MLModel
results will haveFilterVariable
values not equal to the value specified withNE
.Type: String
Length Constraints: Maximum length of 1024.
Pattern:
.*\S.*|^$
Required: No
- NextToken
-
The ID of the page in the paginated results.
Type: String
Required: No
- Prefix
-
A string that is found at the beginning of a variable, such as
Name
orId
.For example, an
MLModel
could have theName
2014-09-09-HolidayGiftMailer
. To search for thisMLModel
, selectName
for theFilterVariable
and any of the following strings for thePrefix
:-
2014-09
-
2014-09-09
-
2014-09-09-Holiday
Type: String
Length Constraints: Maximum length of 1024.
Pattern:
.*\S.*|^$
Required: No
-
- SortOrder
-
A two-value parameter that determines the sequence of the resulting list of
MLModel
.-
asc
- Arranges the list in ascending order (A-Z, 0-9). -
dsc
- Arranges the list in descending order (Z-A, 9-0).
Results are sorted by
FilterVariable
.Type: String
Valid Values:
asc | dsc
Required: No
-
Response Syntax
{
"NextToken": "string",
"Results": [
{
"Algorithm": "string",
"ComputeTime": number,
"CreatedAt": number,
"CreatedByIamUser": "string",
"EndpointInfo": {
"CreatedAt": number,
"EndpointStatus": "string",
"EndpointUrl": "string",
"PeakRequestsPerSecond": number
},
"FinishedAt": number,
"InputDataLocationS3": "string",
"LastUpdatedAt": number,
"Message": "string",
"MLModelId": "string",
"MLModelType": "string",
"Name": "string",
"ScoreThreshold": number,
"ScoreThresholdLastUpdatedAt": number,
"SizeInBytes": number,
"StartedAt": number,
"Status": "string",
"TrainingDataSourceId": "string",
"TrainingParameters": {
"string" : "string"
}
}
]
}
Response Elements
If the action is successful, the service sends back an HTTP 200 response.
The following data is returned in JSON format by the service.
Errors
For information about the errors that are common to all actions, see Common Errors.
- InternalServerException
-
An error on the server occurred when trying to process a request.
HTTP Status Code: 500
- InvalidInputException
-
An error on the client occurred. Typically, the cause is an invalid input value.
HTTP Status Code: 400
Examples
The following is a sample request and response of the DescribeMLModels operation:
This example illustrates one usage of DescribeMLModels.
Sample Request
POST / HTTP/1.1
Host: machinelearning.<region>.<domain>
x-amz-Date: <Date>
Authorization: AWS4-HMAC-SHA256 Credential=<Credential>, SignedHeaders=contenttype;date;host;user-agent;x-amz-date;x-amz-target;x-amzn-requestid,Signature=<Signature>
User-Agent: <UserAgentString>
Content-Type: application/x-amz-json-1.1
Content-Length: <PayloadSizeBytes>
Connection: Keep-Alive
X-Amz-Target: AmazonML_20141212.DescribeMLModels
{
"FilterVariable": "Name",
"Prefix": "ml-",
"SortOrder": "asc",
"Limit": 1
}
Sample Response
HTTP/1.1 200 OK
x-amzn-RequestId: <RequestId>
Content-Type: application/x-amz-json-1.1
Content-Length: <PayloadSizeBytes>
Date: <Date>
{
"NextToken": "\"PredictorId\":\"Spr-ml-model-testing\"}",
"Results": [
{
"CreatedAt": 1422475435.595,
"CreatedByIamUser": "arn:aws:iam::<awsAccountId>:user/username",
"InputDataLocationS3": "s3://bucket/locationToInput/example-data.testing.csv",
"LastUpdatedAt": 1422475709.691,
"MLModelId": "ml-model-testing",
"MLModelType": "MULTICLASS",
"EndpointInfo": {
"CreatedAt": 1424378682.266,
"EndpointStatus": "READY",
"EndpointUrl": "<realtime endpoint from Amazon Machine Learning for ml-model-testing>",
"PeakRequestsPerSecond": 200}
"Name": "ml-model-name",
"Algorithm": "sgd",
"SizeInBytes": 352720,
"Status": "COMPLETED",
"ComputeTime":"185200",
"FinishedAt":"1422475709.691",
"StartedAt":"1422475438.324",
"TrainingDataSourceId": "exampleDataSourceId",
"TrainingParameters":
{
"algorithm": "sgd",
"sgd.l1RegularizationAmount": "0.0",
"sgd.l2RegularizationAmount": "1E-6",
"sgd.maxMLModelSizeInBytes": "33554432",
"sgd.maxPasses": "10"
}
}
]
}
See Also
For more information about using this API in one of the language-specific AWS SDKs, see the following: