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::MachineLearning::UpdateMLModel; use Moose; has MLModelId => (is => 'ro', isa => 'Str', required => 1); has MLModelName => (is => 'ro', isa => 'Str'); has ScoreThreshold => (is => 'ro', isa => 'Num'); use MooseX::ClassAttribute; class_has _api_call => (isa => 'Str', is => 'ro', default => 'UpdateMLModel'); class_has _returns => (isa => 'Str', is => 'ro', default => 'Paws::MachineLearning::UpdateMLModelOutput'); class_has _result_key => (isa => 'Str', is => 'ro'); 1; ### main pod documentation begin ### =head1 NAME Paws::MachineLearning::UpdateMLModel - Arguments for method UpdateMLModel on L =head1 DESCRIPTION This class represents the parameters used for calling the method UpdateMLModel on the L service. Use the attributes of this class as arguments to method UpdateMLModel. You shouldn't make instances of this class. Each attribute should be used as a named argument in the call to UpdateMLModel. =head1 SYNOPSIS my $machinelearning = Paws->service('MachineLearning'); my $UpdateMLModelOutput = $machinelearning->UpdateMLModel( MLModelId => 'MyEntityId', MLModelName => 'MyEntityName', # OPTIONAL ScoreThreshold => 1.0, # OPTIONAL ); # Results: my $MLModelId = $UpdateMLModelOutput->MLModelId; # 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 B MLModelId => Str The ID assigned to the C during creation. =head2 MLModelName => Str A user-supplied name or description of the C. =head2 ScoreThreshold => Num The C used in binary classification C that marks the boundary between a positive prediction and a negative prediction. Output values greater than or equal to the C receive a positive result from the C, such as C. Output values less than the C receive a negative response from the C, such as C. =head1 SEE ALSO This class forms part of L, documenting arguments for method UpdateMLModel in L =head1 BUGS and CONTRIBUTIONS The source code is located here: L Please report bugs to: L =cut