All Downloads are FREE. Search and download functionalities are using the official Maven repository.

com.amazonaws.services.comprehend.model.ClassifierMetadata Maven / Gradle / Ivy

Go to download

The AWS Java SDK for Amazon Comprehend module holds the client classes that are used for communicating with Amazon Comprehend Service

There is a newer version: 1.12.772
Show newest version
/*
 * Copyright 2018-2023 Amazon.com, Inc. or its affiliates. All Rights Reserved.
 * 
 * Licensed under the Apache License, Version 2.0 (the "License"). You may not use this file except in compliance with
 * the License. A copy of the License is located at
 * 
 * http://aws.amazon.com/apache2.0
 * 
 * or in the "license" file accompanying this file. This file is distributed on an "AS IS" BASIS, WITHOUT WARRANTIES OR
 * CONDITIONS OF ANY KIND, either express or implied. See the License for the specific language governing permissions
 * and limitations under the License.
 */
package com.amazonaws.services.comprehend.model;

import java.io.Serializable;
import javax.annotation.Generated;
import com.amazonaws.protocol.StructuredPojo;
import com.amazonaws.protocol.ProtocolMarshaller;

/**
 * 

* Provides information about a document classifier. *

* * @see AWS API * Documentation */ @Generated("com.amazonaws:aws-java-sdk-code-generator") public class ClassifierMetadata implements Serializable, Cloneable, StructuredPojo { /** *

* The number of labels in the input data. *

*/ private Integer numberOfLabels; /** *

* The number of documents in the input data that were used to train the classifier. Typically this is 80 to 90 * percent of the input documents. *

*/ private Integer numberOfTrainedDocuments; /** *

* The number of documents in the input data that were used to test the classifier. Typically this is 10 to 20 * percent of the input documents, up to 10,000 documents. *

*/ private Integer numberOfTestDocuments; /** *

* Describes the result metrics for the test data associated with an documentation classifier. *

*/ private ClassifierEvaluationMetrics evaluationMetrics; /** *

* The number of labels in the input data. *

* * @param numberOfLabels * The number of labels in the input data. */ public void setNumberOfLabels(Integer numberOfLabels) { this.numberOfLabels = numberOfLabels; } /** *

* The number of labels in the input data. *

* * @return The number of labels in the input data. */ public Integer getNumberOfLabels() { return this.numberOfLabels; } /** *

* The number of labels in the input data. *

* * @param numberOfLabels * The number of labels in the input data. * @return Returns a reference to this object so that method calls can be chained together. */ public ClassifierMetadata withNumberOfLabels(Integer numberOfLabels) { setNumberOfLabels(numberOfLabels); return this; } /** *

* The number of documents in the input data that were used to train the classifier. Typically this is 80 to 90 * percent of the input documents. *

* * @param numberOfTrainedDocuments * The number of documents in the input data that were used to train the classifier. Typically this is 80 to * 90 percent of the input documents. */ public void setNumberOfTrainedDocuments(Integer numberOfTrainedDocuments) { this.numberOfTrainedDocuments = numberOfTrainedDocuments; } /** *

* The number of documents in the input data that were used to train the classifier. Typically this is 80 to 90 * percent of the input documents. *

* * @return The number of documents in the input data that were used to train the classifier. Typically this is 80 to * 90 percent of the input documents. */ public Integer getNumberOfTrainedDocuments() { return this.numberOfTrainedDocuments; } /** *

* The number of documents in the input data that were used to train the classifier. Typically this is 80 to 90 * percent of the input documents. *

* * @param numberOfTrainedDocuments * The number of documents in the input data that were used to train the classifier. Typically this is 80 to * 90 percent of the input documents. * @return Returns a reference to this object so that method calls can be chained together. */ public ClassifierMetadata withNumberOfTrainedDocuments(Integer numberOfTrainedDocuments) { setNumberOfTrainedDocuments(numberOfTrainedDocuments); return this; } /** *

* The number of documents in the input data that were used to test the classifier. Typically this is 10 to 20 * percent of the input documents, up to 10,000 documents. *

* * @param numberOfTestDocuments * The number of documents in the input data that were used to test the classifier. Typically this is 10 to * 20 percent of the input documents, up to 10,000 documents. */ public void setNumberOfTestDocuments(Integer numberOfTestDocuments) { this.numberOfTestDocuments = numberOfTestDocuments; } /** *

* The number of documents in the input data that were used to test the classifier. Typically this is 10 to 20 * percent of the input documents, up to 10,000 documents. *

* * @return The number of documents in the input data that were used to test the classifier. Typically this is 10 to * 20 percent of the input documents, up to 10,000 documents. */ public Integer getNumberOfTestDocuments() { return this.numberOfTestDocuments; } /** *

* The number of documents in the input data that were used to test the classifier. Typically this is 10 to 20 * percent of the input documents, up to 10,000 documents. *

* * @param numberOfTestDocuments * The number of documents in the input data that were used to test the classifier. Typically this is 10 to * 20 percent of the input documents, up to 10,000 documents. * @return Returns a reference to this object so that method calls can be chained together. */ public ClassifierMetadata withNumberOfTestDocuments(Integer numberOfTestDocuments) { setNumberOfTestDocuments(numberOfTestDocuments); return this; } /** *

* Describes the result metrics for the test data associated with an documentation classifier. *

* * @param evaluationMetrics * Describes the result metrics for the test data associated with an documentation classifier. */ public void setEvaluationMetrics(ClassifierEvaluationMetrics evaluationMetrics) { this.evaluationMetrics = evaluationMetrics; } /** *

* Describes the result metrics for the test data associated with an documentation classifier. *

* * @return Describes the result metrics for the test data associated with an documentation classifier. */ public ClassifierEvaluationMetrics getEvaluationMetrics() { return this.evaluationMetrics; } /** *

* Describes the result metrics for the test data associated with an documentation classifier. *

* * @param evaluationMetrics * Describes the result metrics for the test data associated with an documentation classifier. * @return Returns a reference to this object so that method calls can be chained together. */ public ClassifierMetadata withEvaluationMetrics(ClassifierEvaluationMetrics evaluationMetrics) { setEvaluationMetrics(evaluationMetrics); return this; } /** * Returns a string representation of this object. This is useful for testing and debugging. Sensitive data will be * redacted from this string using a placeholder value. * * @return A string representation of this object. * * @see java.lang.Object#toString() */ @Override public String toString() { StringBuilder sb = new StringBuilder(); sb.append("{"); if (getNumberOfLabels() != null) sb.append("NumberOfLabels: ").append(getNumberOfLabels()).append(","); if (getNumberOfTrainedDocuments() != null) sb.append("NumberOfTrainedDocuments: ").append(getNumberOfTrainedDocuments()).append(","); if (getNumberOfTestDocuments() != null) sb.append("NumberOfTestDocuments: ").append(getNumberOfTestDocuments()).append(","); if (getEvaluationMetrics() != null) sb.append("EvaluationMetrics: ").append(getEvaluationMetrics()); sb.append("}"); return sb.toString(); } @Override public boolean equals(Object obj) { if (this == obj) return true; if (obj == null) return false; if (obj instanceof ClassifierMetadata == false) return false; ClassifierMetadata other = (ClassifierMetadata) obj; if (other.getNumberOfLabels() == null ^ this.getNumberOfLabels() == null) return false; if (other.getNumberOfLabels() != null && other.getNumberOfLabels().equals(this.getNumberOfLabels()) == false) return false; if (other.getNumberOfTrainedDocuments() == null ^ this.getNumberOfTrainedDocuments() == null) return false; if (other.getNumberOfTrainedDocuments() != null && other.getNumberOfTrainedDocuments().equals(this.getNumberOfTrainedDocuments()) == false) return false; if (other.getNumberOfTestDocuments() == null ^ this.getNumberOfTestDocuments() == null) return false; if (other.getNumberOfTestDocuments() != null && other.getNumberOfTestDocuments().equals(this.getNumberOfTestDocuments()) == false) return false; if (other.getEvaluationMetrics() == null ^ this.getEvaluationMetrics() == null) return false; if (other.getEvaluationMetrics() != null && other.getEvaluationMetrics().equals(this.getEvaluationMetrics()) == false) return false; return true; } @Override public int hashCode() { final int prime = 31; int hashCode = 1; hashCode = prime * hashCode + ((getNumberOfLabels() == null) ? 0 : getNumberOfLabels().hashCode()); hashCode = prime * hashCode + ((getNumberOfTrainedDocuments() == null) ? 0 : getNumberOfTrainedDocuments().hashCode()); hashCode = prime * hashCode + ((getNumberOfTestDocuments() == null) ? 0 : getNumberOfTestDocuments().hashCode()); hashCode = prime * hashCode + ((getEvaluationMetrics() == null) ? 0 : getEvaluationMetrics().hashCode()); return hashCode; } @Override public ClassifierMetadata clone() { try { return (ClassifierMetadata) super.clone(); } catch (CloneNotSupportedException e) { throw new IllegalStateException("Got a CloneNotSupportedException from Object.clone() " + "even though we're Cloneable!", e); } } @com.amazonaws.annotation.SdkInternalApi @Override public void marshall(ProtocolMarshaller protocolMarshaller) { com.amazonaws.services.comprehend.model.transform.ClassifierMetadataMarshaller.getInstance().marshall(this, protocolMarshaller); } }




© 2015 - 2024 Weber Informatics LLC | Privacy Policy