Copyright	(c) 2013-2023 Brendan Hay
License	Mozilla Public License, v. 2.0.
Maintainer	Brendan Hay
Stability	auto-generated
Portability	non-portable (GHC extensions)
Safe Haskell	Safe-Inferred
Language	Haskell2010

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
- filterVariable :: Maybe MLModelFilterVariable
- ge :: Maybe Text
- gt :: Maybe Text
- le :: Maybe Text
- lt :: Maybe Text
- limit :: Maybe Natural
- ne :: Maybe Text
- nextToken :: Maybe Text
- prefix :: Maybe Text
- sortOrder :: Maybe SortOrder
}
newDescribeMLModels :: DescribeMLModels
describeMLModels_eq :: Lens' DescribeMLModels (Maybe Text)
describeMLModels_filterVariable :: Lens' DescribeMLModels (Maybe MLModelFilterVariable)
describeMLModels_ge :: Lens' DescribeMLModels (Maybe Text)
describeMLModels_gt :: Lens' DescribeMLModels (Maybe Text)
describeMLModels_le :: Lens' DescribeMLModels (Maybe Text)
describeMLModels_lt :: Lens' DescribeMLModels (Maybe Text)
describeMLModels_limit :: Lens' DescribeMLModels (Maybe Natural)
describeMLModels_ne :: Lens' DescribeMLModels (Maybe Text)
describeMLModels_nextToken :: Lens' DescribeMLModels (Maybe Text)
describeMLModels_prefix :: Lens' DescribeMLModels (Maybe Text)
describeMLModels_sortOrder :: Lens' DescribeMLModels (Maybe SortOrder)
data DescribeMLModelsResponse = DescribeMLModelsResponse' {
- nextToken :: Maybe Text
- results :: Maybe [MLModel]
- httpStatus :: Int
}
newDescribeMLModelsResponse :: Int -> DescribeMLModelsResponse
describeMLModelsResponse_nextToken :: Lens' DescribeMLModelsResponse (Maybe Text)
describeMLModelsResponse_results :: Lens' DescribeMLModelsResponse (Maybe [MLModel])
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.
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.
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.
gt :: Maybe Text
The greater than operator. The MLModel results will have FilterVariable values that are greater than the value specified with GT.
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.
lt :: Maybe Text
The less than operator. The MLModel results will have FilterVariable values that are less than the value specified with LT.
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.
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.
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
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.

Instances

Instances details

ToJSON DescribeMLModels Source #
Instance details Defined in Amazonka.MachineLearning.DescribeMLModels Methods toJSON :: DescribeMLModels -> Value # toEncoding :: DescribeMLModels -> Encoding # toJSONList :: [DescribeMLModels] -> Value # toEncodingList :: [DescribeMLModels] -> Encoding #
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 #
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 :: (Service -> Service) -> DescribeMLModels -> Request DescribeMLModels # response :: MonadResource m => (ByteStringLazy -> IO ByteStringLazy) -> Service -> Proxy DescribeMLModels -> ClientResponse ClientBody -> m (Either Error (ClientResponse (AWSResponse DescribeMLModels))) #
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 #
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 #
NFData DescribeMLModels Source #
Instance details Defined in Amazonka.MachineLearning.DescribeMLModels Methods rnf :: DescribeMLModels -> () #
Eq DescribeMLModels Source #
Instance details Defined in Amazonka.MachineLearning.DescribeMLModels Methods (==) :: DescribeMLModels -> DescribeMLModels -> Bool # (/=) :: DescribeMLModels -> DescribeMLModels -> Bool #
Hashable DescribeMLModels Source #
Instance details Defined in Amazonka.MachineLearning.DescribeMLModels Methods hashWithSalt :: Int -> DescribeMLModels -> Int # hash :: DescribeMLModels -> Int #
type AWSResponse DescribeMLModels Source #
Instance details Defined in Amazonka.MachineLearning.DescribeMLModels type AWSResponse DescribeMLModels = DescribeMLModelsResponse
type Rep DescribeMLModels Source #
Instance details Defined in Amazonka.MachineLearning.DescribeMLModels type Rep DescribeMLModels = D1 ('MetaData "DescribeMLModels" "Amazonka.MachineLearning.DescribeMLModels" "amazonka-ml-2.0-A3JLJ63WvmfHxGBBIqhdRA" 'False) (C1 ('MetaCons "DescribeMLModels'" 'PrefixI 'True) (((S1 ('MetaSel ('Just "eq") 'NoSourceUnpackedness 'NoSourceStrictness 'DecidedStrict) (Rec0 (Maybe Text)) :: S1 ('MetaSel ('Just "filterVariable") 'NoSourceUnpackedness 'NoSourceStrictness 'DecidedStrict) (Rec0 (Maybe MLModelFilterVariable))) :: (S1 ('MetaSel ('Just "ge") 'NoSourceUnpackedness 'NoSourceStrictness 'DecidedStrict) (Rec0 (Maybe Text)) :: (S1 ('MetaSel ('Just "gt") 'NoSourceUnpackedness 'NoSourceStrictness 'DecidedStrict) (Rec0 (Maybe Text)) :: S1 ('MetaSel ('Just "le") 'NoSourceUnpackedness 'NoSourceStrictness 'DecidedStrict) (Rec0 (Maybe Text))))) :: ((S1 ('MetaSel ('Just "lt") 'NoSourceUnpackedness 'NoSourceStrictness 'DecidedStrict) (Rec0 (Maybe Text)) :: (S1 ('MetaSel ('Just "limit") 'NoSourceUnpackedness 'NoSourceStrictness 'DecidedStrict) (Rec0 (Maybe Natural)) :: S1 ('MetaSel ('Just "ne") 'NoSourceUnpackedness 'NoSourceStrictness 'DecidedStrict) (Rec0 (Maybe Text)))) :: (S1 ('MetaSel ('Just "nextToken") 'NoSourceUnpackedness 'NoSourceStrictness 'DecidedStrict) (Rec0 (Maybe Text)) :: (S1 ('MetaSel ('Just "prefix") 'NoSourceUnpackedness 'NoSourceStrictness 'DecidedStrict) (Rec0 (Maybe Text)) :: S1 ('MetaSel ('Just "sortOrder") 'NoSourceUnpackedness 'NoSourceStrictness 'DecidedStrict) (Rec0 (Maybe SortOrder)))))))

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: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: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: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: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.

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

DescribeMLModels, describeMLModels_nextToken - The ID of the page in the paginated results.

$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: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.

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_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_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_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_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.

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_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_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_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_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.

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

Instances

Instances details

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 #
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 #
NFData DescribeMLModelsResponse Source #
Instance details Defined in Amazonka.MachineLearning.DescribeMLModels Methods rnf :: DescribeMLModelsResponse -> () #
Eq DescribeMLModelsResponse Source #
Instance details Defined in Amazonka.MachineLearning.DescribeMLModels Methods (==) :: DescribeMLModelsResponse -> DescribeMLModelsResponse -> Bool # (/=) :: DescribeMLModelsResponse -> DescribeMLModelsResponse -> Bool #
type Rep DescribeMLModelsResponse Source #
Instance details Defined in Amazonka.MachineLearning.DescribeMLModels type Rep DescribeMLModelsResponse = D1 ('MetaData "DescribeMLModelsResponse" "Amazonka.MachineLearning.DescribeMLModels" "amazonka-ml-2.0-A3JLJ63WvmfHxGBBIqhdRA" 'False) (C1 ('MetaCons "DescribeMLModelsResponse'" 'PrefixI 'True) (S1 ('MetaSel ('Just "nextToken") 'NoSourceUnpackedness 'NoSourceStrictness 'DecidedStrict) (Rec0 (Maybe Text)) :: (S1 ('MetaSel ('Just "results") 'NoSourceUnpackedness 'NoSourceStrictness 'DecidedStrict) (Rec0 (Maybe [MLModel])) :: 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:

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

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

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

Response Lenses

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

A list of MLModel that meet the search criteria.

describeMLModelsResponse_httpStatus :: Lens' DescribeMLModelsResponse Int Source #

The response's http status code.