PNG  IHDR;IDATxܻn0K )(pA 7LeG{ §㻢|ذaÆ 6lذaÆ 6lذaÆ 6lom$^yذag5bÆ 6lذaÆ 6lذa{ 6lذaÆ `}HFkm,mӪôô! x|'ܢ˟;E:9&ᶒ}{v]n&6 h_tڠ͵-ҫZ;Z$.Pkž)!o>}leQfJTu іچ\X=8Rن4`Vwl>nG^is"ms$ui?wbs[m6K4O.4%/bC%t Mז -lG6mrz2s%9s@-k9=)kB5\+͂Zsٲ Rn~GRC wIcIn7jJhۛNCS|j08yiHKֶۛkɈ+;SzL/F*\Ԕ#"5m2[S=gnaPeғL lذaÆ 6l^ḵaÆ 6lذaÆ 6lذa; _ذaÆ 6lذaÆ 6lذaÆ RIENDB` package Paws::FraudDetector::CreateDetectorVersion; use Moose; has Description => (is => 'ro', isa => 'Str', traits => ['NameInRequest'], request_name => 'description' ); has DetectorId => (is => 'ro', isa => 'Str', traits => ['NameInRequest'], request_name => 'detectorId' , required => 1); has ExternalModelEndpoints => (is => 'ro', isa => 'ArrayRef[Str|Undef]', traits => ['NameInRequest'], request_name => 'externalModelEndpoints' ); has ModelVersions => (is => 'ro', isa => 'ArrayRef[Paws::FraudDetector::ModelVersion]', traits => ['NameInRequest'], request_name => 'modelVersions' ); has RuleExecutionMode => (is => 'ro', isa => 'Str', traits => ['NameInRequest'], request_name => 'ruleExecutionMode' ); has Rules => (is => 'ro', isa => 'ArrayRef[Paws::FraudDetector::Rule]', traits => ['NameInRequest'], request_name => 'rules' , required => 1); has Tags => (is => 'ro', isa => 'ArrayRef[Paws::FraudDetector::Tag]', traits => ['NameInRequest'], request_name => 'tags' ); use MooseX::ClassAttribute; class_has _api_call => (isa => 'Str', is => 'ro', default => 'CreateDetectorVersion'); class_has _returns => (isa => 'Str', is => 'ro', default => 'Paws::FraudDetector::CreateDetectorVersionResult'); class_has _result_key => (isa => 'Str', is => 'ro'); 1; ### main pod documentation begin ### =head1 NAME Paws::FraudDetector::CreateDetectorVersion - Arguments for method CreateDetectorVersion on L =head1 DESCRIPTION This class represents the parameters used for calling the method CreateDetectorVersion on the L service. Use the attributes of this class as arguments to method CreateDetectorVersion. You shouldn't make instances of this class. Each attribute should be used as a named argument in the call to CreateDetectorVersion. =head1 SYNOPSIS my $frauddetector = Paws->service('FraudDetector'); my $CreateDetectorVersionResult = $frauddetector->CreateDetectorVersion( DetectorId => 'Myidentifier', Rules => [ { DetectorId => 'Myidentifier', # min: 1, max: 64 RuleId => 'Myidentifier', # min: 1, max: 64 RuleVersion => 'MywholeNumberVersionString', # min: 1, max: 5 }, ... ], Description => 'Mydescription', # OPTIONAL ExternalModelEndpoints => [ 'Mystring', ... ], # OPTIONAL ModelVersions => [ { ModelId => 'MymodelIdentifier', # min: 1, max: 64 ModelType => 'ONLINE_FRAUD_INSIGHTS', # values: ONLINE_FRAUD_INSIGHTS ModelVersionNumber => 'MynonEmptyString', # min: 1 Arn => 'MyfraudDetectorArn', # min: 1, max: 256; OPTIONAL }, ... ], # OPTIONAL RuleExecutionMode => 'ALL_MATCHED', # OPTIONAL Tags => [ { Key => 'MytagKey', # min: 1, max: 128 Value => 'MytagValue', # max: 256 }, ... ], # OPTIONAL ); # Results: my $DetectorId = $CreateDetectorVersionResult->DetectorId; my $DetectorVersionId = $CreateDetectorVersionResult->DetectorVersionId; my $Status = $CreateDetectorVersionResult->Status; # Returns a L object. Values for attributes that are native types (Int, String, Float, etc) can passed as-is (scalar values). Values for complex Types (objects) can be passed as a HashRef. The keys and values of the hashref will be used to instance the underlying object. For the AWS API documentation, see L =head1 ATTRIBUTES =head2 Description => Str The description of the detector version. =head2 B DetectorId => Str The ID of the detector under which you want to create a new version. =head2 ExternalModelEndpoints => ArrayRef[Str|Undef] The Amazon Sagemaker model endpoints to include in the detector version. =head2 ModelVersions => ArrayRef[L] The model versions to include in the detector version. =head2 RuleExecutionMode => Str The rule execution mode for the rules included in the detector version. You can define and edit the rule mode at the detector version level, when it is in draft status. If you specify C, Amazon Fraud Detector evaluates rules sequentially, first to last, stopping at the first matched rule. Amazon Fraud dectector then provides the outcomes for that single rule. If you specifiy C, Amazon Fraud Detector evaluates all rules and returns the outcomes for all matched rules. The default behavior is C. Valid values are: C<"ALL_MATCHED">, C<"FIRST_MATCHED"> =head2 B Rules => ArrayRef[L] The rules to include in the detector version. =head2 Tags => ArrayRef[L] A collection of key and value pairs. =head1 SEE ALSO This class forms part of L, documenting arguments for method CreateDetectorVersion in L =head1 BUGS and CONTRIBUTIONS The source code is located here: L Please report bugs to: L =cut