Copyright	(c) 2013-2021 Brendan Hay
License	Mozilla Public License, v. 2.0.
Maintainer	Brendan Hay <brendan.g.hay+amazonka@gmail.com>
Stability	auto-generated
Portability	non-portable (GHC extensions)
Safe Haskell	None

Amazonka.MachineLearning.DescribeMLModels

Contents

Creating a Request
Request Lenses
Destructuring the Response
Response Lenses

Description

Returns a list of MLModel that match the search criteria in the request.

This operation returns paginated results.

Synopsis

data DescribeMLModels = DescribeMLModels' {
- eq :: Maybe Text
- ge :: Maybe Text
- prefix :: Maybe Text
- gt :: Maybe Text
- ne :: Maybe Text
- nextToken :: Maybe Text
- sortOrder :: Maybe SortOrder
- limit :: Maybe Natural
- lt :: Maybe Text
- filterVariable :: Maybe MLModelFilterVariable
- le :: Maybe Text
}
newDescribeMLModels :: DescribeMLModels
describeMLModels_eq :: Lens' DescribeMLModels (Maybe Text)
describeMLModels_ge :: Lens' DescribeMLModels (Maybe Text)
describeMLModels_prefix :: Lens' DescribeMLModels (Maybe Text)
describeMLModels_gt :: Lens' DescribeMLModels (Maybe Text)
describeMLModels_ne :: Lens' DescribeMLModels (Maybe Text)
describeMLModels_nextToken :: Lens' DescribeMLModels (Maybe Text)
describeMLModels_sortOrder :: Lens' DescribeMLModels (Maybe SortOrder)
describeMLModels_limit :: Lens' DescribeMLModels (Maybe Natural)
describeMLModels_lt :: Lens' DescribeMLModels (Maybe Text)
describeMLModels_filterVariable :: Lens' DescribeMLModels (Maybe MLModelFilterVariable)
describeMLModels_le :: Lens' DescribeMLModels (Maybe Text)
data DescribeMLModelsResponse = DescribeMLModelsResponse' {
- results :: Maybe [MLModel]
- nextToken :: Maybe Text
- httpStatus :: Int
}
newDescribeMLModelsResponse :: Int -> DescribeMLModelsResponse
describeMLModelsResponse_results :: Lens' DescribeMLModelsResponse (Maybe [MLModel])
describeMLModelsResponse_nextToken :: Lens' DescribeMLModelsResponse (Maybe Text)
describeMLModelsResponse_httpStatus :: Lens' DescribeMLModelsResponse Int

Creating a Request

data DescribeMLModels Source #

See: newDescribeMLModels smart constructor.

Constructors

DescribeMLModels'

Fields

eq :: Maybe Text
The equal to operator. The MLModel results will have FilterVariable values that exactly match the value specified with EQ.
ge :: Maybe Text
The greater than or equal to operator. The MLModel results will have FilterVariable values that are greater than or equal to the value specified with GE.
prefix :: Maybe Text
A string that is found at the beginning of a variable, such as Name or Id.
For example, an MLModel could have the Name 2014-09-09-HolidayGiftMailer. To search for this MLModel, select Name for the FilterVariable and any of the following strings for the Prefix:
- 2014-09
- 2014-09-09
- 2014-09-09-Holiday
gt :: Maybe Text
The greater than operator. The MLModel results will have FilterVariable values that are greater than the value specified with GT.
ne :: Maybe Text
The not equal to operator. The MLModel results will have FilterVariable values not equal to the value specified with NE.
nextToken :: Maybe Text
The ID of the page in the paginated results.
sortOrder :: Maybe 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.
limit :: Maybe Natural
The number of pages of information to include in the result. The range of acceptable values is 1 through 100. The default value is 100.
lt :: Maybe Text
The less than operator. The MLModel results will have FilterVariable values that are less than the value specified with LT.
filterVariable :: Maybe MLModelFilterVariable
Use one of the following variables to filter a list of MLModel:
- CreatedAt - Sets the search criteria to MLModel creation date.
- Status - Sets the search criteria to MLModel status.
- Name - Sets the search criteria to the contents of MLModel ____ Name.
- IAMUser - Sets the search criteria to the user account that invoked the MLModel creation.
- TrainingDataSourceId - Sets the search criteria to the DataSource used to train one or more MLModel.
- RealtimeEndpointStatus - Sets the search criteria to the MLModel real-time endpoint status.
- MLModelType - Sets the search criteria to MLModel type: binary, regression, or multi-class.
- Algorithm - Sets the search criteria to the algorithm that the MLModel uses.
- TrainingDataURI - Sets the search criteria to the data file(s) used in training a MLModel. The URL can identify either a file or an Amazon Simple Storage Service (Amazon S3) bucket or directory.
le :: Maybe Text
The less than or equal to operator. The MLModel results will have FilterVariable values that are less than or equal to the value specified with LE.

Instances

Instances details

Eq DescribeMLModels Source #
Instance details Defined in Amazonka.MachineLearning.DescribeMLModels Methods (==) :: DescribeMLModels -> DescribeMLModels -> Bool # (/=) :: DescribeMLModels -> DescribeMLModels -> Bool #
Read DescribeMLModels Source #
Instance details Defined in Amazonka.MachineLearning.DescribeMLModels Methods readsPrec :: Int -> ReadS DescribeMLModels # readList :: ReadS [DescribeMLModels] # readPrec :: ReadPrec DescribeMLModels # readListPrec :: ReadPrec [DescribeMLModels] #
Show DescribeMLModels Source #
Instance details Defined in Amazonka.MachineLearning.DescribeMLModels Methods showsPrec :: Int -> DescribeMLModels -> ShowS # show :: DescribeMLModels -> String # showList :: [DescribeMLModels] -> ShowS #
Generic DescribeMLModels Source #
Instance details Defined in Amazonka.MachineLearning.DescribeMLModels Associated Types type Rep DescribeMLModels :: Type -> Type # Methods from :: DescribeMLModels -> Rep DescribeMLModels x # to :: Rep DescribeMLModels x -> DescribeMLModels #
NFData DescribeMLModels Source #
Instance details Defined in Amazonka.MachineLearning.DescribeMLModels Methods rnf :: DescribeMLModels -> () #
Hashable DescribeMLModels Source #
Instance details Defined in Amazonka.MachineLearning.DescribeMLModels Methods hashWithSalt :: Int -> DescribeMLModels -> Int # hash :: DescribeMLModels -> Int #
ToJSON DescribeMLModels Source #
Instance details Defined in Amazonka.MachineLearning.DescribeMLModels Methods toJSON :: DescribeMLModels -> Value # toEncoding :: DescribeMLModels -> Encoding # toJSONList :: [DescribeMLModels] -> Value # toEncodingList :: [DescribeMLModels] -> Encoding #
AWSPager DescribeMLModels Source #
Instance details Defined in Amazonka.MachineLearning.DescribeMLModels Methods page :: DescribeMLModels -> AWSResponse DescribeMLModels -> Maybe DescribeMLModels #
AWSRequest DescribeMLModels Source #
Instance details Defined in Amazonka.MachineLearning.DescribeMLModels Associated Types type AWSResponse DescribeMLModels # Methods request :: DescribeMLModels -> Request DescribeMLModels # response :: MonadResource m => Logger -> Service -> Proxy DescribeMLModels -> ClientResponse ClientBody -> m (Either Error (ClientResponse (AWSResponse DescribeMLModels))) #
ToHeaders DescribeMLModels Source #
Instance details Defined in Amazonka.MachineLearning.DescribeMLModels Methods toHeaders :: DescribeMLModels -> [Header] #
ToPath DescribeMLModels Source #
Instance details Defined in Amazonka.MachineLearning.DescribeMLModels Methods toPath :: DescribeMLModels -> ByteString #
ToQuery DescribeMLModels Source #
Instance details Defined in Amazonka.MachineLearning.DescribeMLModels Methods toQuery :: DescribeMLModels -> QueryString #
type Rep DescribeMLModels Source #
Instance details Defined in Amazonka.MachineLearning.DescribeMLModels type Rep DescribeMLModels = D1 ('MetaData "DescribeMLModels" "Amazonka.MachineLearning.DescribeMLModels" "libZSservicesZSamazonka-mlZSamazonka-ml" 'False) (C1 ('MetaCons "DescribeMLModels'" 'PrefixI 'True) (((S1 ('MetaSel ('Just "eq") 'NoSourceUnpackedness 'NoSourceStrictness 'DecidedStrict) (Rec0 (Maybe Text)) :: S1 ('MetaSel ('Just "ge") 'NoSourceUnpackedness 'NoSourceStrictness 'DecidedStrict) (Rec0 (Maybe Text))) :: (S1 ('MetaSel ('Just "prefix") 'NoSourceUnpackedness 'NoSourceStrictness 'DecidedStrict) (Rec0 (Maybe Text)) :: (S1 ('MetaSel ('Just "gt") 'NoSourceUnpackedness 'NoSourceStrictness 'DecidedStrict) (Rec0 (Maybe Text)) :: S1 ('MetaSel ('Just "ne") 'NoSourceUnpackedness 'NoSourceStrictness 'DecidedStrict) (Rec0 (Maybe Text))))) :: ((S1 ('MetaSel ('Just "nextToken") 'NoSourceUnpackedness 'NoSourceStrictness 'DecidedStrict) (Rec0 (Maybe Text)) :: (S1 ('MetaSel ('Just "sortOrder") 'NoSourceUnpackedness 'NoSourceStrictness 'DecidedStrict) (Rec0 (Maybe SortOrder)) :: S1 ('MetaSel ('Just "limit") 'NoSourceUnpackedness 'NoSourceStrictness 'DecidedStrict) (Rec0 (Maybe Natural)))) :: (S1 ('MetaSel ('Just "lt") 'NoSourceUnpackedness 'NoSourceStrictness 'DecidedStrict) (Rec0 (Maybe Text)) :: (S1 ('MetaSel ('Just "filterVariable") 'NoSourceUnpackedness 'NoSourceStrictness 'DecidedStrict) (Rec0 (Maybe MLModelFilterVariable)) :: S1 ('MetaSel ('Just "le") 'NoSourceUnpackedness 'NoSourceStrictness 'DecidedStrict) (Rec0 (Maybe Text)))))))
type AWSResponse DescribeMLModels Source #
Instance details Defined in Amazonka.MachineLearning.DescribeMLModels type AWSResponse DescribeMLModels = DescribeMLModelsResponse

newDescribeMLModels :: DescribeMLModels Source #

Create a value of DescribeMLModels with all optional fields omitted.

Use generic-lens or optics to modify other optional fields.

The following record fields are available, with the corresponding lenses provided for backwards compatibility:

$sel:eq:DescribeMLModels', describeMLModels_eq - The equal to operator. The MLModel results will have FilterVariable values that exactly match the value specified with EQ.

$sel:ge:DescribeMLModels', describeMLModels_ge - The greater than or equal to operator. The MLModel results will have FilterVariable values that are greater than or equal to the value specified with GE.

$sel:prefix:DescribeMLModels', describeMLModels_prefix - A string that is found at the beginning of a variable, such as Name or Id.

For example, an MLModel could have the Name 2014-09-09-HolidayGiftMailer. To search for this MLModel, select Name for the FilterVariable and any of the following strings for the Prefix:

2014-09
2014-09-09
2014-09-09-Holiday

$sel:gt:DescribeMLModels', describeMLModels_gt - The greater than operator. The MLModel results will have FilterVariable values that are greater than the value specified with GT.

$sel:ne:DescribeMLModels', describeMLModels_ne - The not equal to operator. The MLModel results will have FilterVariable values not equal to the value specified with NE.

$sel:nextToken:DescribeMLModels', describeMLModels_nextToken - The ID of the page in the paginated results.

$sel:sortOrder:DescribeMLModels', describeMLModels_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.

$sel:limit:DescribeMLModels', describeMLModels_limit - The number of pages of information to include in the result. The range of acceptable values is 1 through 100. The default value is 100.

$sel:lt:DescribeMLModels', describeMLModels_lt - The less than operator. The MLModel results will have FilterVariable values that are less than the value specified with LT.

$sel:filterVariable:DescribeMLModels', describeMLModels_filterVariable - Use one of the following variables to filter a list of MLModel:

CreatedAt - Sets the search criteria to MLModel creation date.
Status - Sets the search criteria to MLModel status.
Name - Sets the search criteria to the contents of MLModel ____ Name.
IAMUser - Sets the search criteria to the user account that invoked the MLModel creation.
TrainingDataSourceId - Sets the search criteria to the DataSource used to train one or more MLModel.
RealtimeEndpointStatus - Sets the search criteria to the MLModel real-time endpoint status.
MLModelType - Sets the search criteria to MLModel type: binary, regression, or multi-class.
Algorithm - Sets the search criteria to the algorithm that the MLModel uses.
TrainingDataURI - Sets the search criteria to the data file(s) used in training a MLModel. The URL can identify either a file or an Amazon Simple Storage Service (Amazon S3) bucket or directory.

$sel:le:DescribeMLModels', describeMLModels_le - The less than or equal to operator. The MLModel results will have FilterVariable values that are less than or equal to the value specified with LE.

Request Lenses

describeMLModels_eq :: Lens' DescribeMLModels (Maybe Text) Source #

The equal to operator. The MLModel results will have FilterVariable values that exactly match the value specified with EQ.

describeMLModels_ge :: Lens' DescribeMLModels (Maybe Text) Source #

The greater than or equal to operator. The MLModel results will have FilterVariable values that are greater than or equal to the value specified with GE.

describeMLModels_prefix :: Lens' DescribeMLModels (Maybe Text) Source #

A string that is found at the beginning of a variable, such as Name or Id.

For example, an MLModel could have the Name 2014-09-09-HolidayGiftMailer. To search for this MLModel, select Name for the FilterVariable and any of the following strings for the Prefix:

2014-09
2014-09-09
2014-09-09-Holiday

describeMLModels_gt :: Lens' DescribeMLModels (Maybe Text) Source #

The greater than operator. The MLModel results will have FilterVariable values that are greater than the value specified with GT.

describeMLModels_ne :: Lens' DescribeMLModels (Maybe Text) Source #

The not equal to operator. The MLModel results will have FilterVariable values not equal to the value specified with NE.

describeMLModels_nextToken :: Lens' DescribeMLModels (Maybe Text) Source #

The ID of the page in the paginated results.

describeMLModels_sortOrder :: Lens' DescribeMLModels (Maybe SortOrder) Source #

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.

describeMLModels_limit :: Lens' DescribeMLModels (Maybe Natural) Source #

The number of pages of information to include in the result. The range of acceptable values is 1 through 100. The default value is 100.

describeMLModels_lt :: Lens' DescribeMLModels (Maybe Text) Source #

The less than operator. The MLModel results will have FilterVariable values that are less than the value specified with LT.

describeMLModels_filterVariable :: Lens' DescribeMLModels (Maybe MLModelFilterVariable) Source #

Use one of the following variables to filter a list of MLModel:

CreatedAt - Sets the search criteria to MLModel creation date.
Status - Sets the search criteria to MLModel status.
Name - Sets the search criteria to the contents of MLModel ____ Name.
IAMUser - Sets the search criteria to the user account that invoked the MLModel creation.
TrainingDataSourceId - Sets the search criteria to the DataSource used to train one or more MLModel.
RealtimeEndpointStatus - Sets the search criteria to the MLModel real-time endpoint status.
MLModelType - Sets the search criteria to MLModel type: binary, regression, or multi-class.
Algorithm - Sets the search criteria to the algorithm that the MLModel uses.
TrainingDataURI - Sets the search criteria to the data file(s) used in training a MLModel. The URL can identify either a file or an Amazon Simple Storage Service (Amazon S3) bucket or directory.

describeMLModels_le :: Lens' DescribeMLModels (Maybe Text) Source #

The less than or equal to operator. The MLModel results will have FilterVariable values that are less than or equal to the value specified with LE.

Destructuring the Response

data DescribeMLModelsResponse Source #

Represents the output of a DescribeMLModels operation. The content is essentially a list of MLModel.

See: newDescribeMLModelsResponse smart constructor.

Constructors

DescribeMLModelsResponse'
Fields results :: Maybe [MLModel] A list of `MLModel` that meet the search criteria. nextToken :: Maybe Text The ID of the next page in the paginated results that indicates at least one more page follows. httpStatus :: Int The response's http status code.

Instances

Instances details

Eq DescribeMLModelsResponse Source #
Instance details Defined in Amazonka.MachineLearning.DescribeMLModels Methods (==) :: DescribeMLModelsResponse -> DescribeMLModelsResponse -> Bool # (/=) :: DescribeMLModelsResponse -> DescribeMLModelsResponse -> Bool #
Read DescribeMLModelsResponse Source #
Instance details Defined in Amazonka.MachineLearning.DescribeMLModels Methods readsPrec :: Int -> ReadS DescribeMLModelsResponse # readList :: ReadS [DescribeMLModelsResponse] # readPrec :: ReadPrec DescribeMLModelsResponse # readListPrec :: ReadPrec [DescribeMLModelsResponse] #
Show DescribeMLModelsResponse Source #
Instance details Defined in Amazonka.MachineLearning.DescribeMLModels Methods showsPrec :: Int -> DescribeMLModelsResponse -> ShowS # show :: DescribeMLModelsResponse -> String # showList :: [DescribeMLModelsResponse] -> ShowS #
Generic DescribeMLModelsResponse Source #
Instance details Defined in Amazonka.MachineLearning.DescribeMLModels Associated Types type Rep DescribeMLModelsResponse :: Type -> Type # Methods from :: DescribeMLModelsResponse -> Rep DescribeMLModelsResponse x # to :: Rep DescribeMLModelsResponse x -> DescribeMLModelsResponse #
NFData DescribeMLModelsResponse Source #
Instance details Defined in Amazonka.MachineLearning.DescribeMLModels Methods rnf :: DescribeMLModelsResponse -> () #
type Rep DescribeMLModelsResponse Source #
Instance details Defined in Amazonka.MachineLearning.DescribeMLModels type Rep DescribeMLModelsResponse = D1 ('MetaData "DescribeMLModelsResponse" "Amazonka.MachineLearning.DescribeMLModels" "libZSservicesZSamazonka-mlZSamazonka-ml" 'False) (C1 ('MetaCons "DescribeMLModelsResponse'" 'PrefixI 'True) (S1 ('MetaSel ('Just "results") 'NoSourceUnpackedness 'NoSourceStrictness 'DecidedStrict) (Rec0 (Maybe [MLModel])) :: (S1 ('MetaSel ('Just "nextToken") 'NoSourceUnpackedness 'NoSourceStrictness 'DecidedStrict) (Rec0 (Maybe Text)) :: S1 ('MetaSel ('Just "httpStatus") 'NoSourceUnpackedness 'NoSourceStrictness 'DecidedStrict) (Rec0 Int))))

newDescribeMLModelsResponse Source #

Arguments

:: Int	`$sel:httpStatus:DescribeMLModelsResponse'`
-> DescribeMLModelsResponse

Create a value of DescribeMLModelsResponse with all optional fields omitted.

Use generic-lens or optics to modify other optional fields.

The following record fields are available, with the corresponding lenses provided for backwards compatibility:

$sel:results:DescribeMLModelsResponse', describeMLModelsResponse_results - A list of MLModel that meet the search criteria.

$sel:nextToken:DescribeMLModels', describeMLModelsResponse_nextToken - The ID of the next page in the paginated results that indicates at least one more page follows.

$sel:httpStatus:DescribeMLModelsResponse', describeMLModelsResponse_httpStatus - The response's http status code.

Response Lenses

describeMLModelsResponse_results :: Lens' DescribeMLModelsResponse (Maybe [MLModel]) Source #

A list of MLModel that meet the search criteria.

describeMLModelsResponse_nextToken :: Lens' DescribeMLModelsResponse (Maybe Text) Source #

The ID of the next page in the paginated results that indicates at least one more page follows.

describeMLModelsResponse_httpStatus :: Lens' DescribeMLModelsResponse Int Source #

The response's http status code.