forecastservice_create_dataset {paws.machine.learning} | R Documentation |
Creates an Amazon Forecast dataset
Description
Creates an Amazon Forecast dataset. The information about the dataset that you provide helps Forecast understand how to consume the data for model training. This includes the following:
See https://www.paws-r-sdk.com/docs/forecastservice_create_dataset/ for full documentation.
Usage
forecastservice_create_dataset(
DatasetName,
Domain,
DatasetType,
DataFrequency = NULL,
Schema,
EncryptionConfig = NULL,
Tags = NULL
)
Arguments
DatasetName |
[required] A name for the dataset. |
Domain |
[required] The domain associated with the dataset. When you add a dataset to a
dataset group, this value and the value specified for the The |
DatasetType |
[required] The dataset type. Valid values depend on the chosen |
DataFrequency |
The frequency of data collection. This parameter is required for RELATED_TIME_SERIES datasets. Valid intervals are an integer followed by Y (Year), M (Month), W (Week), D (Day), H (Hour), and min (Minute). For example, "1D" indicates every day and "15min" indicates every 15 minutes. You cannot specify a value that would overlap with the next larger frequency. That means, for example, you cannot specify a frequency of 60 minutes, because that is equivalent to 1 hour. The valid values for each frequency are the following:
Thus, if you want every other week forecasts, specify "2W". Or, if you want quarterly forecasts, you specify "3M". |
Schema |
[required] The schema for the dataset. The schema attributes and their order must
match the fields in your data. The dataset |
EncryptionConfig |
An Key Management Service (KMS) key and the Identity and Access Management (IAM) role that Amazon Forecast can assume to access the key. |
Tags |
The optional metadata that you apply to the dataset to help you categorize and organize them. Each tag consists of a key and an optional value, both of which you define. The following basic restrictions apply to tags:
|