Copyright | (c) 2013-2023 Brendan Hay |
---|---|
License | Mozilla Public License, v. 2.0. |
Maintainer | Brendan Hay |
Stability | auto-generated |
Portability | non-portable (GHC extensions) |
Safe Haskell | Safe-Inferred |
Language | Haskell2010 |
Synopsis
- data DocumentClassifierInputDataConfig = DocumentClassifierInputDataConfig' {}
- newDocumentClassifierInputDataConfig :: DocumentClassifierInputDataConfig
- documentClassifierInputDataConfig_augmentedManifests :: Lens' DocumentClassifierInputDataConfig (Maybe [AugmentedManifestsListItem])
- documentClassifierInputDataConfig_dataFormat :: Lens' DocumentClassifierInputDataConfig (Maybe DocumentClassifierDataFormat)
- documentClassifierInputDataConfig_labelDelimiter :: Lens' DocumentClassifierInputDataConfig (Maybe Text)
- documentClassifierInputDataConfig_s3Uri :: Lens' DocumentClassifierInputDataConfig (Maybe Text)
- documentClassifierInputDataConfig_testS3Uri :: Lens' DocumentClassifierInputDataConfig (Maybe Text)
Documentation
data DocumentClassifierInputDataConfig Source #
The input properties for training a document classifier.
For more information on how the input file is formatted, see Preparing training data in the Comprehend Developer Guide.
See: newDocumentClassifierInputDataConfig
smart constructor.
DocumentClassifierInputDataConfig' | |
|
Instances
newDocumentClassifierInputDataConfig :: DocumentClassifierInputDataConfig Source #
Create a value of DocumentClassifierInputDataConfig
with all optional fields omitted.
Use generic-lens or optics to modify other optional fields.
The following record fields are available, with the corresponding lenses provided for backwards compatibility:
$sel:augmentedManifests:DocumentClassifierInputDataConfig'
, documentClassifierInputDataConfig_augmentedManifests
- A list of augmented manifest files that provide training data for your
custom model. An augmented manifest file is a labeled dataset that is
produced by Amazon SageMaker Ground Truth.
This parameter is required if you set DataFormat
to
AUGMENTED_MANIFEST
.
$sel:dataFormat:DocumentClassifierInputDataConfig'
, documentClassifierInputDataConfig_dataFormat
- The format of your training data:
COMPREHEND_CSV
: A two-column CSV file, where labels are provided in the first column, and documents are provided in the second. If you use this value, you must provide theS3Uri
parameter in your request.AUGMENTED_MANIFEST
: A labeled dataset that is produced by Amazon SageMaker Ground Truth. This file is in JSON lines format. Each line is a complete JSON object that contains a training document and its associated labels.If you use this value, you must provide the
AugmentedManifests
parameter in your request.
If you don't specify a value, Amazon Comprehend uses COMPREHEND_CSV
as the default.
$sel:labelDelimiter:DocumentClassifierInputDataConfig'
, documentClassifierInputDataConfig_labelDelimiter
- Indicates the delimiter used to separate each label for training a
multi-label classifier. The default delimiter between labels is a pipe
(|). You can use a different character as a delimiter (if it's an
allowed character) by specifying it under Delimiter for labels. If the
training documents use a delimiter other than the default or the
delimiter you specify, the labels on that line will be combined to make
a single unique label, such as LABELLABELLABEL.
DocumentClassifierInputDataConfig
, documentClassifierInputDataConfig_s3Uri
- The Amazon S3 URI for the input data. The S3 bucket must be in the same
region as the API endpoint that you are calling. The URI can point to a
single input file or it can provide the prefix for a collection of input
files.
For example, if you use the URI S3://bucketName/prefix
, if the
prefix is a single file, Amazon Comprehend uses that file as input. If
more than one file begins with the prefix, Amazon Comprehend uses all of
them as input.
This parameter is required if you set DataFormat
to COMPREHEND_CSV
.
$sel:testS3Uri:DocumentClassifierInputDataConfig'
, documentClassifierInputDataConfig_testS3Uri
- This specifies the Amazon S3 location where the test annotations for an
entity recognizer are located. The URI must be in the same AWS Region as
the API endpoint that you are calling.
documentClassifierInputDataConfig_augmentedManifests :: Lens' DocumentClassifierInputDataConfig (Maybe [AugmentedManifestsListItem]) Source #
A list of augmented manifest files that provide training data for your custom model. An augmented manifest file is a labeled dataset that is produced by Amazon SageMaker Ground Truth.
This parameter is required if you set DataFormat
to
AUGMENTED_MANIFEST
.
documentClassifierInputDataConfig_dataFormat :: Lens' DocumentClassifierInputDataConfig (Maybe DocumentClassifierDataFormat) Source #
The format of your training data:
COMPREHEND_CSV
: A two-column CSV file, where labels are provided in the first column, and documents are provided in the second. If you use this value, you must provide theS3Uri
parameter in your request.AUGMENTED_MANIFEST
: A labeled dataset that is produced by Amazon SageMaker Ground Truth. This file is in JSON lines format. Each line is a complete JSON object that contains a training document and its associated labels.If you use this value, you must provide the
AugmentedManifests
parameter in your request.
If you don't specify a value, Amazon Comprehend uses COMPREHEND_CSV
as the default.
documentClassifierInputDataConfig_labelDelimiter :: Lens' DocumentClassifierInputDataConfig (Maybe Text) Source #
Indicates the delimiter used to separate each label for training a multi-label classifier. The default delimiter between labels is a pipe (|). You can use a different character as a delimiter (if it's an allowed character) by specifying it under Delimiter for labels. If the training documents use a delimiter other than the default or the delimiter you specify, the labels on that line will be combined to make a single unique label, such as LABELLABELLABEL.
documentClassifierInputDataConfig_s3Uri :: Lens' DocumentClassifierInputDataConfig (Maybe Text) Source #
The Amazon S3 URI for the input data. The S3 bucket must be in the same region as the API endpoint that you are calling. The URI can point to a single input file or it can provide the prefix for a collection of input files.
For example, if you use the URI S3://bucketName/prefix
, if the
prefix is a single file, Amazon Comprehend uses that file as input. If
more than one file begins with the prefix, Amazon Comprehend uses all of
them as input.
This parameter is required if you set DataFormat
to COMPREHEND_CSV
.
documentClassifierInputDataConfig_testS3Uri :: Lens' DocumentClassifierInputDataConfig (Maybe Text) Source #
This specifies the Amazon S3 location where the test annotations for an entity recognizer are located. The URI must be in the same AWS Region as the API endpoint that you are calling.