# Train custom classifiers (API)
<a name="train-custom-classifier-api"></a>

To create and train a custom classifier, use the [CreateDocumentClassifier](https://docs.aws.amazon.com/comprehend/latest/APIReference/API_CreateDocumentClassifier.html) operation.

You can monitor the progress of the request using the [DescribeDocumentClassifier](https://docs.aws.amazon.com/comprehend/latest/APIReference/API_DescribeDocumentClassifier.html) operation. After the `Status` field transitions to `TRAINED`, you can use the classifier to classify documents. If the status is `TRAINED_WITH_WARNINGS`, review the skipped files folder in the [Classifier training output](train-classifier-output.md) from the `CreateDocumentClassifier` operation.

**Topics**
+ [Training custom classification using the AWS Command Line Interface](#get-started-api-customclass-cli)
+ [Using the AWS SDK for Java or SDK for Python](#get-started-api-customclass-java)

## Training custom classification using the AWS Command Line Interface
<a name="get-started-api-customclass-cli"></a>

The following examples show how to use the `CreateDocumentClassifier` operation, the `DescribeDocumentClassificationJob` operation, and other custom classifier APIs with the AWS CLI. 

The examples are formatted for Unix, Linux, and macOS. For Windows, replace the backslash (\$1) Unix continuation character at the end of each line with a caret (^).

Create a plain-text custom classifier using the `create-document-classifier` operation.

```
aws comprehend create-document-classifier \
     --region region \
     --document-classifier-name testDelete \
     --language-code en \
     --input-data-config S3Uri=s3://S3Bucket/docclass/file name \
     --data-access-role-arn arn:aws:iam::account number:role/testFlywheelDataAccess
```

To create a native custom classifier, provide the following additional parameters in the `create-document-classifier` request.

1. DocumentType: set the value to SEMI\$1STRUCTURED\$1DOCUMENT.

1. Documents: the S3 location for the training documents (and, optionally, the test documents).

1. OutputDataConfig: provide the S3 location for the output documents (and an optional KMS key). 

1. DocumentReaderConfig: Optional field for text extraction settings.

```
aws comprehend create-document-classifier \
     --region region \
     --document-classifier-name testDelete \
     --language-code en \
     --input-data-config 
          S3Uri=s3://S3Bucket/docclass/file name \
           DocumentType \
             Documents  \
     --output-data-config S3Uri=s3://S3Bucket/docclass/file name \
     --data-access-role-arn arn:aws:iam::account number:role/testFlywheelDataAccess
```

Get information on a custom classifier with the document classifier ARN using the `DescribeDocumentClassifier` operation.

```
aws comprehend describe-document-classifier \
     --region region \
     --document-classifier-arn arn:aws:comprehend:region:account number:document-classifier/file name
```

Delete a custom classifier using the `DeleteDocumentClassifier` operation.

```
aws comprehend delete-document-classifier \
     --region region \
     --document-classifier-arn arn:aws:comprehend:region:account number:document-classifier/testDelete
```

List all custom classifiers in the account using the `ListDocumentClassifiers` operation.

```
aws comprehend list-document-classifiers
     --region region
```

## Using the AWS SDK for Java or SDK for Python
<a name="get-started-api-customclass-java"></a>

For SDK examples of how to create and train a custom classifier , see [Use `CreateDocumentClassifier` with an AWS SDK or CLI](example_comprehend_CreateDocumentClassifier_section.md).