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Paws::Forecast::HyperParameterTuningJobConfig(3) User Contributed Perl Documentation Paws::Forecast::HyperParameterTuningJobConfig(3)

Paws::Forecast::HyperParameterTuningJobConfig

This class represents one of two things:

Arguments in a call to a service

Use the attributes of this class as arguments to methods. You shouldn't make instances of this class. Each attribute should be used as a named argument in the calls that expect this type of object.

As an example, if Att1 is expected to be a Paws::Forecast::HyperParameterTuningJobConfig object:

  $service_obj->Method(Att1 => { ParameterRanges => $value, ..., ParameterRanges => $value  });

Results returned from an API call

Use accessors for each attribute. If Att1 is expected to be an Paws::Forecast::HyperParameterTuningJobConfig object:

  $result = $service_obj->Method(...);
  $result->Att1->ParameterRanges

Configuration information for a hyperparameter tuning job. You specify this object in the CreatePredictor request.

A hyperparameter is a parameter that governs the model training process. You set hyperparameters before training starts, unlike model parameters, which are determined during training. The values of the hyperparameters effect which values are chosen for the model parameters.

In a hyperparameter tuning job, Amazon Forecast chooses the set of hyperparameter values that optimize a specified metric. Forecast accomplishes this by running many training jobs over a range of hyperparameter values. The optimum set of values depends on the algorithm, the training data, and the specified metric objective.

Specifies the ranges of valid values for the hyperparameters.

This class forms part of Paws, describing an object used in Paws::Forecast

The source code is located here: <https://github.com/pplu/aws-sdk-perl>

Please report bugs to: <https://github.com/pplu/aws-sdk-perl/issues>

2022-06-01 perl v5.40.2

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