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/AWS1/CL_CPDDOCCLIFIERINPDAT00

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.

CONSTRUCTOR

IMPORTING

Optional arguments:

iv_dataformat TYPE /AWS1/CPDDOCCLASSIFIERDATAFMT /AWS1/CPDDOCCLASSIFIERDATAFMT

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 the S3Uri 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.

iv_s3uri TYPE /AWS1/CPDS3URI /AWS1/CPDS3URI

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.

iv_tests3uri TYPE /AWS1/CPDS3URI /AWS1/CPDS3URI

This specifies the Amazon S3 location that contains the test annotations for the document classifier. The URI must be in the same Amazon Web Services Region as the API endpoint that you are calling.

iv_labeldelimiter TYPE /AWS1/CPDLABELDELIMITER /AWS1/CPDLABELDELIMITER

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.

it_augmentedmanifests TYPE /AWS1/CL_CPDAUGMENTEDMANIFES00=>TT_DOCCLIFIERAUGMENTEDMANIFE00 TT_DOCCLIFIERAUGMENTEDMANIFE00

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.

iv_documenttype TYPE /AWS1/CPDDOCCLIFIERDOCTYPEFMT /AWS1/CPDDOCCLIFIERDOCTYPEFMT

The type of input documents for training the model. Provide plain-text documents to create a plain-text model, and provide semi-structured documents to create a native document model.

io_documents TYPE REF TO /AWS1/CL_CPDDOCCLASSIFIERDOCS /AWS1/CL_CPDDOCCLASSIFIERDOCS

The S3 location of the training documents.
This parameter is required in a request to create a native document model.

io_documentreaderconfig TYPE REF TO /AWS1/CL_CPDDOCREADERCONFIG /AWS1/CL_CPDDOCREADERCONFIG

DocumentReaderConfig

Queryable Attributes

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 the S3Uri 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.

Accessible with the following methods

Method Description
GET_DATAFORMAT() Getter for DATAFORMAT, with configurable default
ASK_DATAFORMAT() Getter for DATAFORMAT w/ exceptions if field has no value
HAS_DATAFORMAT() Determine if DATAFORMAT has a value

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.

Accessible with the following methods

Method Description
GET_S3URI() Getter for S3URI, with configurable default
ASK_S3URI() Getter for S3URI w/ exceptions if field has no value
HAS_S3URI() Determine if S3URI has a value

TestS3Uri

This specifies the Amazon S3 location that contains the test annotations for the document classifier. The URI must be in the same Amazon Web Services Region as the API endpoint that you are calling.

Accessible with the following methods

Method Description
GET_TESTS3URI() Getter for TESTS3URI, with configurable default
ASK_TESTS3URI() Getter for TESTS3URI w/ exceptions if field has no value
HAS_TESTS3URI() Determine if TESTS3URI has a value

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.

Accessible with the following methods

Method Description
GET_LABELDELIMITER() Getter for LABELDELIMITER, with configurable default
ASK_LABELDELIMITER() Getter for LABELDELIMITER w/ exceptions if field has no valu
HAS_LABELDELIMITER() Determine if LABELDELIMITER has a value

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.

Accessible with the following methods

Method Description
GET_AUGMENTEDMANIFESTS() Getter for AUGMENTEDMANIFESTS, with configurable default
ASK_AUGMENTEDMANIFESTS() Getter for AUGMENTEDMANIFESTS w/ exceptions if field has no
HAS_AUGMENTEDMANIFESTS() Determine if AUGMENTEDMANIFESTS has a value

DocumentType

The type of input documents for training the model. Provide plain-text documents to create a plain-text model, and provide semi-structured documents to create a native document model.

Accessible with the following methods

Method Description
GET_DOCUMENTTYPE() Getter for DOCUMENTTYPE, with configurable default
ASK_DOCUMENTTYPE() Getter for DOCUMENTTYPE w/ exceptions if field has no value
HAS_DOCUMENTTYPE() Determine if DOCUMENTTYPE has a value

Documents

The S3 location of the training documents.
This parameter is required in a request to create a native document model.

Accessible with the following methods

Method Description
GET_DOCUMENTS() Getter for DOCUMENTS

DocumentReaderConfig

DocumentReaderConfig

Accessible with the following methods

Method Description
GET_DOCUMENTREADERCONFIG() Getter for DOCUMENTREADERCONFIG