public ClarifyInferenceConfig withLabelHeaders(String... labelHeaders) {
        if (this.labelHeaders == null) {
            setLabelHeaders(new java.util.ArrayList<String>(labelHeaders.length));
        }
        for (String ele : labelHeaders) {
            this.labelHeaders.add(ele);
        }
        return this;
    }
<p>
For multiclass classification problems, the label headers are the names of the classes. Otherwise, the label
header is the name of the predicted label. These are used to help readability for the output of the
<code>InvokeEndpoint</code> API. See the <a href=
"https://docs.aws.amazon.com/sagemaker/latest/dg/clarify-online-explainability-invoke-endpoint.html#clarify-online-explainability-response"
>response</a> section under <b>Invoke the endpoint</b> in the Developer Guide for more information. If there are
no label headers in the model container output, provide them manually using this parameter.
</p>
<p>
<b>NOTE:</b> This method appends the values to the existing list (if any). Use
{@link #setLabelHeaders(java.util.Collection)} or {@link #withLabelHeaders(java.util.Collection)} if you want to
override the existing values.
</p>

@param labelHeaders
       For multiclass classification problems, the label headers are the names of the classes. Otherwise, the
       label header is the name of the predicted label. These are used to help readability for the output of the
       <code>InvokeEndpoint</code> API. See the <a href=
       "https://docs.aws.amazon.com/sagemaker/latest/dg/clarify-online-explainability-invoke-endpoint.html#clarify-online-explainability-response"
       >response</a> section under <b>Invoke the endpoint</b> in the Developer Guide for more information. If
       there are no label headers in the model container output, provide them manually using this parameter.
@return Returns a reference to this object so that method calls can be chained together.
aws-java-sdk-sagemaker/src/main/java/com/amazonaws/services/sagemaker/model/ClarifyInferenceConfig.java