package Paws::LookoutEquipment::CreateModel; use Moose; has ClientToken => (is => 'ro', isa => 'Str', required => 1); has DataPreProcessingConfiguration => (is => 'ro', isa => 'Paws::LookoutEquipment::DataPreProcessingConfiguration'); has DatasetName => (is => 'ro', isa => 'Str', required => 1); has DatasetSchema => (is => 'ro', isa => 'Paws::LookoutEquipment::DatasetSchema'); has EvaluationDataEndTime => (is => 'ro', isa => 'Str'); has EvaluationDataStartTime => (is => 'ro', isa => 'Str'); has LabelsInputConfiguration => (is => 'ro', isa => 'Paws::LookoutEquipment::LabelsInputConfiguration'); has ModelName => (is => 'ro', isa => 'Str', required => 1); has RoleArn => (is => 'ro', isa => 'Str'); has ServerSideKmsKeyId => (is => 'ro', isa => 'Str'); has Tags => (is => 'ro', isa => 'ArrayRef[Paws::LookoutEquipment::Tag]'); has TrainingDataEndTime => (is => 'ro', isa => 'Str'); has TrainingDataStartTime => (is => 'ro', isa => 'Str'); use MooseX::ClassAttribute; class_has _api_call => (isa => 'Str', is => 'ro', default => 'CreateModel'); class_has _returns => (isa => 'Str', is => 'ro', default => 'Paws::LookoutEquipment::CreateModelResponse'); class_has _result_key => (isa => 'Str', is => 'ro'); 1; ### main pod documentation begin ### =head1 NAME Paws::LookoutEquipment::CreateModel - Arguments for method CreateModel on L =head1 DESCRIPTION This class represents the parameters used for calling the method CreateModel on the L service. Use the attributes of this class as arguments to method CreateModel. You shouldn't make instances of this class. Each attribute should be used as a named argument in the call to CreateModel. =head1 SYNOPSIS my $lookoutequipment = Paws->service('LookoutEquipment'); my $CreateModelResponse = $lookoutequipment->CreateModel( ClientToken => 'MyIdempotenceToken', DatasetName => 'MyDatasetIdentifier', ModelName => 'MyModelName', DataPreProcessingConfiguration => { TargetSamplingRate => 'PT1S' , # values: PT1S, PT5S, PT10S, PT15S, PT30S, PT1M, PT5M, PT10M, PT15M, PT30M, PT1H; OPTIONAL }, # OPTIONAL DatasetSchema => { InlineDataSchema => 'MyInlineDataSchema', # min: 1, max: 1000000; OPTIONAL }, # OPTIONAL EvaluationDataEndTime => '1970-01-01T01:00:00', # OPTIONAL EvaluationDataStartTime => '1970-01-01T01:00:00', # OPTIONAL LabelsInputConfiguration => { S3InputConfiguration => { Bucket => 'MyS3Bucket', # min: 3, max: 63 Prefix => 'MyS3Prefix', # max: 1024; OPTIONAL }, }, # OPTIONAL RoleArn => 'MyIamRoleArn', # OPTIONAL ServerSideKmsKeyId => 'MyNameOrArn', # OPTIONAL Tags => [ { Key => 'MyTagKey', # min: 1, max: 128 Value => 'MyTagValue', # max: 256 }, ... ], # OPTIONAL TrainingDataEndTime => '1970-01-01T01:00:00', # OPTIONAL TrainingDataStartTime => '1970-01-01T01:00:00', # OPTIONAL ); # Results: my $ModelArn = $CreateModelResponse->ModelArn; my $Status = $CreateModelResponse->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 B ClientToken => Str A unique identifier for the request. If you do not set the client request token, Amazon Lookout for Equipment generates one. =head2 DataPreProcessingConfiguration => L The configuration is the C, which is the sampling rate of the data after post processing by Amazon Lookout for Equipment. For example, if you provide data that has been collected at a 1 second level and you want the system to resample the data at a 1 minute rate before training, the C is 1 minute. When providing a value for the C, you must attach the prefix "PT" to the rate you want. The value for a 1 second rate is therefore I, the value for a 15 minute rate is I, and the value for a 1 hour rate is I =head2 B DatasetName => Str The name of the dataset for the ML model being created. =head2 DatasetSchema => L The data schema for the ML model being created. =head2 EvaluationDataEndTime => Str Indicates the time reference in the dataset that should be used to end the subset of evaluation data for the ML model. =head2 EvaluationDataStartTime => Str Indicates the time reference in the dataset that should be used to begin the subset of evaluation data for the ML model. =head2 LabelsInputConfiguration => L The input configuration for the labels being used for the ML model that's being created. =head2 B ModelName => Str The name for the ML model to be created. =head2 RoleArn => Str The Amazon Resource Name (ARN) of a role with permission to access the data source being used to create the ML model. =head2 ServerSideKmsKeyId => Str Provides the identifier of the AWS KMS customer master key (CMK) used to encrypt model data by Amazon Lookout for Equipment. =head2 Tags => ArrayRef[L] Any tags associated with the ML model being created. =head2 TrainingDataEndTime => Str Indicates the time reference in the dataset that should be used to end the subset of training data for the ML model. =head2 TrainingDataStartTime => Str Indicates the time reference in the dataset that should be used to begin the subset of training data for the ML model. =head1 SEE ALSO This class forms part of L, documenting arguments for method CreateModel in L =head1 BUGS and CONTRIBUTIONS The source code is located here: L Please report bugs to: L =cut