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The AWS Java SDK for Amazon Machine Learning module holds the client classes that is used for communicating with Amazon Machine Learning Service

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/*
 * Copyright 2010-2016 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.machinelearning.model;

import java.io.Serializable;

/**
 * 

* Represents the output of GetEvaluation operation. *

*

* The content consists of the detailed metadata and data file information and * the current status of the Evaluation. *

*/ public class Evaluation implements Serializable, Cloneable { /** *

* The ID that is assigned to the Evaluation at creation. *

*/ private String evaluationId; /** *

* The ID of the MLModel that is the focus of the evaluation. *

*/ private String mLModelId; /** *

* The ID of the DataSource that is used to evaluate the * MLModel. *

*/ private String evaluationDataSourceId; /** *

* The location and name of the data in Amazon Simple Storage Server (Amazon * S3) that is used in the evaluation. *

*/ private String inputDataLocationS3; /** *

* The AWS user account that invoked the evaluation. The account type can be * either an AWS root account or an AWS Identity and Access Management (IAM) * user account. *

*/ private String createdByIamUser; /** *

* The time that the Evaluation was created. The time is * expressed in epoch time. *

*/ private java.util.Date createdAt; /** *

* The time of the most recent edit to the Evaluation. The time * is expressed in epoch time. *

*/ private java.util.Date lastUpdatedAt; /** *

* A user-supplied name or description of the Evaluation. *

*/ private String name; /** *

* The status of the evaluation. This element can have one of the following * values: *

*
    *
  • PENDING - Amazon Machine Learning (Amazon ML) submitted * a request to evaluate an MLModel.
  • *
  • INPROGRESS - The evaluation is underway.
  • *
  • FAILED - The request to evaluate an MLModel * did not run to completion. It is not usable.
  • *
  • COMPLETED - The evaluation process completed * successfully.
  • *
  • DELETED - The Evaluation is marked as * deleted. It is not usable.
  • *
*/ private String status; /** *

* Measurements of how well the MLModel performed, using * observations referenced by the DataSource. One of the * following metrics is returned, based on the type of the MLModel: *

*
    *
  • *

    * BinaryAUC: A binary MLModel uses the Area Under the Curve * (AUC) technique to measure performance. *

    *
  • *
  • *

    * RegressionRMSE: A regression MLModel uses the Root Mean * Square Error (RMSE) technique to measure performance. RMSE measures the * difference between predicted and actual values for a single variable. *

    *
  • *
  • *

    * MulticlassAvgFScore: A multiclass MLModel uses the F1 score * technique to measure performance. *

    *
  • *
*

* For more information about performance metrics, please see the Amazon * Machine Learning Developer Guide. *

*/ private PerformanceMetrics performanceMetrics; /** *

* A description of the most recent details about evaluating the * MLModel. *

*/ private String message; /** *

* The ID that is assigned to the Evaluation at creation. *

* * @param evaluationId * The ID that is assigned to the Evaluation at * creation. */ public void setEvaluationId(String evaluationId) { this.evaluationId = evaluationId; } /** *

* The ID that is assigned to the Evaluation at creation. *

* * @return The ID that is assigned to the Evaluation at * creation. */ public String getEvaluationId() { return this.evaluationId; } /** *

* The ID that is assigned to the Evaluation at creation. *

* * @param evaluationId * The ID that is assigned to the Evaluation at * creation. * @return Returns a reference to this object so that method calls can be * chained together. */ public Evaluation withEvaluationId(String evaluationId) { setEvaluationId(evaluationId); return this; } /** *

* The ID of the MLModel that is the focus of the evaluation. *

* * @param mLModelId * The ID of the MLModel that is the focus of the * evaluation. */ public void setMLModelId(String mLModelId) { this.mLModelId = mLModelId; } /** *

* The ID of the MLModel that is the focus of the evaluation. *

* * @return The ID of the MLModel that is the focus of the * evaluation. */ public String getMLModelId() { return this.mLModelId; } /** *

* The ID of the MLModel that is the focus of the evaluation. *

* * @param mLModelId * The ID of the MLModel that is the focus of the * evaluation. * @return Returns a reference to this object so that method calls can be * chained together. */ public Evaluation withMLModelId(String mLModelId) { setMLModelId(mLModelId); return this; } /** *

* The ID of the DataSource that is used to evaluate the * MLModel. *

* * @param evaluationDataSourceId * The ID of the DataSource that is used to evaluate the * MLModel. */ public void setEvaluationDataSourceId(String evaluationDataSourceId) { this.evaluationDataSourceId = evaluationDataSourceId; } /** *

* The ID of the DataSource that is used to evaluate the * MLModel. *

* * @return The ID of the DataSource that is used to evaluate * the MLModel. */ public String getEvaluationDataSourceId() { return this.evaluationDataSourceId; } /** *

* The ID of the DataSource that is used to evaluate the * MLModel. *

* * @param evaluationDataSourceId * The ID of the DataSource that is used to evaluate the * MLModel. * @return Returns a reference to this object so that method calls can be * chained together. */ public Evaluation withEvaluationDataSourceId(String evaluationDataSourceId) { setEvaluationDataSourceId(evaluationDataSourceId); return this; } /** *

* The location and name of the data in Amazon Simple Storage Server (Amazon * S3) that is used in the evaluation. *

* * @param inputDataLocationS3 * The location and name of the data in Amazon Simple Storage Server * (Amazon S3) that is used in the evaluation. */ public void setInputDataLocationS3(String inputDataLocationS3) { this.inputDataLocationS3 = inputDataLocationS3; } /** *

* The location and name of the data in Amazon Simple Storage Server (Amazon * S3) that is used in the evaluation. *

* * @return The location and name of the data in Amazon Simple Storage Server * (Amazon S3) that is used in the evaluation. */ public String getInputDataLocationS3() { return this.inputDataLocationS3; } /** *

* The location and name of the data in Amazon Simple Storage Server (Amazon * S3) that is used in the evaluation. *

* * @param inputDataLocationS3 * The location and name of the data in Amazon Simple Storage Server * (Amazon S3) that is used in the evaluation. * @return Returns a reference to this object so that method calls can be * chained together. */ public Evaluation withInputDataLocationS3(String inputDataLocationS3) { setInputDataLocationS3(inputDataLocationS3); return this; } /** *

* The AWS user account that invoked the evaluation. The account type can be * either an AWS root account or an AWS Identity and Access Management (IAM) * user account. *

* * @param createdByIamUser * The AWS user account that invoked the evaluation. The account type * can be either an AWS root account or an AWS Identity and Access * Management (IAM) user account. */ public void setCreatedByIamUser(String createdByIamUser) { this.createdByIamUser = createdByIamUser; } /** *

* The AWS user account that invoked the evaluation. The account type can be * either an AWS root account or an AWS Identity and Access Management (IAM) * user account. *

* * @return The AWS user account that invoked the evaluation. The account * type can be either an AWS root account or an AWS Identity and * Access Management (IAM) user account. */ public String getCreatedByIamUser() { return this.createdByIamUser; } /** *

* The AWS user account that invoked the evaluation. The account type can be * either an AWS root account or an AWS Identity and Access Management (IAM) * user account. *

* * @param createdByIamUser * The AWS user account that invoked the evaluation. The account type * can be either an AWS root account or an AWS Identity and Access * Management (IAM) user account. * @return Returns a reference to this object so that method calls can be * chained together. */ public Evaluation withCreatedByIamUser(String createdByIamUser) { setCreatedByIamUser(createdByIamUser); return this; } /** *

* The time that the Evaluation was created. The time is * expressed in epoch time. *

* * @param createdAt * The time that the Evaluation was created. The time is * expressed in epoch time. */ public void setCreatedAt(java.util.Date createdAt) { this.createdAt = createdAt; } /** *

* The time that the Evaluation was created. The time is * expressed in epoch time. *

* * @return The time that the Evaluation was created. The time * is expressed in epoch time. */ public java.util.Date getCreatedAt() { return this.createdAt; } /** *

* The time that the Evaluation was created. The time is * expressed in epoch time. *

* * @param createdAt * The time that the Evaluation was created. The time is * expressed in epoch time. * @return Returns a reference to this object so that method calls can be * chained together. */ public Evaluation withCreatedAt(java.util.Date createdAt) { setCreatedAt(createdAt); return this; } /** *

* The time of the most recent edit to the Evaluation. The time * is expressed in epoch time. *

* * @param lastUpdatedAt * The time of the most recent edit to the Evaluation. * The time is expressed in epoch time. */ public void setLastUpdatedAt(java.util.Date lastUpdatedAt) { this.lastUpdatedAt = lastUpdatedAt; } /** *

* The time of the most recent edit to the Evaluation. The time * is expressed in epoch time. *

* * @return The time of the most recent edit to the Evaluation. * The time is expressed in epoch time. */ public java.util.Date getLastUpdatedAt() { return this.lastUpdatedAt; } /** *

* The time of the most recent edit to the Evaluation. The time * is expressed in epoch time. *

* * @param lastUpdatedAt * The time of the most recent edit to the Evaluation. * The time is expressed in epoch time. * @return Returns a reference to this object so that method calls can be * chained together. */ public Evaluation withLastUpdatedAt(java.util.Date lastUpdatedAt) { setLastUpdatedAt(lastUpdatedAt); return this; } /** *

* A user-supplied name or description of the Evaluation. *

* * @param name * A user-supplied name or description of the Evaluation * . */ public void setName(String name) { this.name = name; } /** *

* A user-supplied name or description of the Evaluation. *

* * @return A user-supplied name or description of the * Evaluation. */ public String getName() { return this.name; } /** *

* A user-supplied name or description of the Evaluation. *

* * @param name * A user-supplied name or description of the Evaluation * . * @return Returns a reference to this object so that method calls can be * chained together. */ public Evaluation withName(String name) { setName(name); return this; } /** *

* The status of the evaluation. This element can have one of the following * values: *

*
    *
  • PENDING - Amazon Machine Learning (Amazon ML) submitted * a request to evaluate an MLModel.
  • *
  • INPROGRESS - The evaluation is underway.
  • *
  • FAILED - The request to evaluate an MLModel * did not run to completion. It is not usable.
  • *
  • COMPLETED - The evaluation process completed * successfully.
  • *
  • DELETED - The Evaluation is marked as * deleted. It is not usable.
  • *
* * @param status * The status of the evaluation. This element can have one of the * following values:

*
    *
  • PENDING - Amazon Machine Learning (Amazon ML) * submitted a request to evaluate an MLModel.
  • *
  • INPROGRESS - The evaluation is underway.
  • *
  • FAILED - The request to evaluate an * MLModel did not run to completion. It is not usable.
  • *
  • COMPLETED - The evaluation process completed * successfully.
  • *
  • DELETED - The Evaluation is marked * as deleted. It is not usable.
  • * @see EntityStatus */ public void setStatus(String status) { this.status = status; } /** *

    * The status of the evaluation. This element can have one of the following * values: *

    *
      *
    • PENDING - Amazon Machine Learning (Amazon ML) submitted * a request to evaluate an MLModel.
    • *
    • INPROGRESS - The evaluation is underway.
    • *
    • FAILED - The request to evaluate an MLModel * did not run to completion. It is not usable.
    • *
    • COMPLETED - The evaluation process completed * successfully.
    • *
    • DELETED - The Evaluation is marked as * deleted. It is not usable.
    • *
    * * @return The status of the evaluation. This element can have one of the * following values:

    *
      *
    • PENDING - Amazon Machine Learning (Amazon ML) * submitted a request to evaluate an MLModel.
    • *
    • INPROGRESS - The evaluation is underway.
    • *
    • FAILED - The request to evaluate an * MLModel did not run to completion. It is not usable. *
    • *
    • COMPLETED - The evaluation process completed * successfully.
    • *
    • DELETED - The Evaluation is marked * as deleted. It is not usable.
    • * @see EntityStatus */ public String getStatus() { return this.status; } /** *

      * The status of the evaluation. This element can have one of the following * values: *

      *
        *
      • PENDING - Amazon Machine Learning (Amazon ML) submitted * a request to evaluate an MLModel.
      • *
      • INPROGRESS - The evaluation is underway.
      • *
      • FAILED - The request to evaluate an MLModel * did not run to completion. It is not usable.
      • *
      • COMPLETED - The evaluation process completed * successfully.
      • *
      • DELETED - The Evaluation is marked as * deleted. It is not usable.
      • *
      * * @param status * The status of the evaluation. This element can have one of the * following values:

      *
        *
      • PENDING - Amazon Machine Learning (Amazon ML) * submitted a request to evaluate an MLModel.
      • *
      • INPROGRESS - The evaluation is underway.
      • *
      • FAILED - The request to evaluate an * MLModel did not run to completion. It is not usable.
      • *
      • COMPLETED - The evaluation process completed * successfully.
      • *
      • DELETED - The Evaluation is marked * as deleted. It is not usable.
      • * @return Returns a reference to this object so that method calls can be * chained together. * @see EntityStatus */ public Evaluation withStatus(String status) { setStatus(status); return this; } /** *

        * The status of the evaluation. This element can have one of the following * values: *

        *
          *
        • PENDING - Amazon Machine Learning (Amazon ML) submitted * a request to evaluate an MLModel.
        • *
        • INPROGRESS - The evaluation is underway.
        • *
        • FAILED - The request to evaluate an MLModel * did not run to completion. It is not usable.
        • *
        • COMPLETED - The evaluation process completed * successfully.
        • *
        • DELETED - The Evaluation is marked as * deleted. It is not usable.
        • *
        * * @param status * The status of the evaluation. This element can have one of the * following values:

        *
          *
        • PENDING - Amazon Machine Learning (Amazon ML) * submitted a request to evaluate an MLModel.
        • *
        • INPROGRESS - The evaluation is underway.
        • *
        • FAILED - The request to evaluate an * MLModel did not run to completion. It is not usable.
        • *
        • COMPLETED - The evaluation process completed * successfully.
        • *
        • DELETED - The Evaluation is marked * as deleted. It is not usable.
        • * @see EntityStatus */ public void setStatus(EntityStatus status) { this.status = status.toString(); } /** *

          * The status of the evaluation. This element can have one of the following * values: *

          *
            *
          • PENDING - Amazon Machine Learning (Amazon ML) submitted * a request to evaluate an MLModel.
          • *
          • INPROGRESS - The evaluation is underway.
          • *
          • FAILED - The request to evaluate an MLModel * did not run to completion. It is not usable.
          • *
          • COMPLETED - The evaluation process completed * successfully.
          • *
          • DELETED - The Evaluation is marked as * deleted. It is not usable.
          • *
          * * @param status * The status of the evaluation. This element can have one of the * following values:

          *
            *
          • PENDING - Amazon Machine Learning (Amazon ML) * submitted a request to evaluate an MLModel.
          • *
          • INPROGRESS - The evaluation is underway.
          • *
          • FAILED - The request to evaluate an * MLModel did not run to completion. It is not usable.
          • *
          • COMPLETED - The evaluation process completed * successfully.
          • *
          • DELETED - The Evaluation is marked * as deleted. It is not usable.
          • * @return Returns a reference to this object so that method calls can be * chained together. * @see EntityStatus */ public Evaluation withStatus(EntityStatus status) { setStatus(status); return this; } /** *

            * Measurements of how well the MLModel performed, using * observations referenced by the DataSource. One of the * following metrics is returned, based on the type of the MLModel: *

            *
              *
            • *

              * BinaryAUC: A binary MLModel uses the Area Under the Curve * (AUC) technique to measure performance. *

              *
            • *
            • *

              * RegressionRMSE: A regression MLModel uses the Root Mean * Square Error (RMSE) technique to measure performance. RMSE measures the * difference between predicted and actual values for a single variable. *

              *
            • *
            • *

              * MulticlassAvgFScore: A multiclass MLModel uses the F1 score * technique to measure performance. *

              *
            • *
            *

            * For more information about performance metrics, please see the Amazon * Machine Learning Developer Guide. *

            * * @param performanceMetrics * Measurements of how well the MLModel performed, using * observations referenced by the DataSource. One of the * following metrics is returned, based on the type of the MLModel: *

            *
              *
            • *

              * BinaryAUC: A binary MLModel uses the Area Under the * Curve (AUC) technique to measure performance. *

              *
            • *
            • *

              * RegressionRMSE: A regression MLModel uses the Root * Mean Square Error (RMSE) technique to measure performance. RMSE * measures the difference between predicted and actual values for a * single variable. *

              *
            • *
            • *

              * MulticlassAvgFScore: A multiclass MLModel uses the F1 * score technique to measure performance. *

              *
            • *
            *

            * For more information about performance metrics, please see the Amazon * Machine Learning Developer Guide. */ public void setPerformanceMetrics(PerformanceMetrics performanceMetrics) { this.performanceMetrics = performanceMetrics; } /** *

            * Measurements of how well the MLModel performed, using * observations referenced by the DataSource. One of the * following metrics is returned, based on the type of the MLModel: *

            *
              *
            • *

              * BinaryAUC: A binary MLModel uses the Area Under the Curve * (AUC) technique to measure performance. *

              *
            • *
            • *

              * RegressionRMSE: A regression MLModel uses the Root Mean * Square Error (RMSE) technique to measure performance. RMSE measures the * difference between predicted and actual values for a single variable. *

              *
            • *
            • *

              * MulticlassAvgFScore: A multiclass MLModel uses the F1 score * technique to measure performance. *

              *
            • *
            *

            * For more information about performance metrics, please see the Amazon * Machine Learning Developer Guide. *

            * * @return Measurements of how well the MLModel performed, * using observations referenced by the DataSource. One * of the following metrics is returned, based on the type of the * MLModel:

            *
              *
            • *

              * BinaryAUC: A binary MLModel uses the Area Under the * Curve (AUC) technique to measure performance. *

              *
            • *
            • *

              * RegressionRMSE: A regression MLModel uses the Root * Mean Square Error (RMSE) technique to measure performance. RMSE * measures the difference between predicted and actual values for a * single variable. *

              *
            • *
            • *

              * MulticlassAvgFScore: A multiclass MLModel uses the * F1 score technique to measure performance. *

              *
            • *
            *

            * For more information about performance metrics, please see the Amazon * Machine Learning Developer Guide. */ public PerformanceMetrics getPerformanceMetrics() { return this.performanceMetrics; } /** *

            * Measurements of how well the MLModel performed, using * observations referenced by the DataSource. One of the * following metrics is returned, based on the type of the MLModel: *

            *
              *
            • *

              * BinaryAUC: A binary MLModel uses the Area Under the Curve * (AUC) technique to measure performance. *

              *
            • *
            • *

              * RegressionRMSE: A regression MLModel uses the Root Mean * Square Error (RMSE) technique to measure performance. RMSE measures the * difference between predicted and actual values for a single variable. *

              *
            • *
            • *

              * MulticlassAvgFScore: A multiclass MLModel uses the F1 score * technique to measure performance. *

              *
            • *
            *

            * For more information about performance metrics, please see the Amazon * Machine Learning Developer Guide. *

            * * @param performanceMetrics * Measurements of how well the MLModel performed, using * observations referenced by the DataSource. One of the * following metrics is returned, based on the type of the MLModel: *

            *
              *
            • *

              * BinaryAUC: A binary MLModel uses the Area Under the * Curve (AUC) technique to measure performance. *

              *
            • *
            • *

              * RegressionRMSE: A regression MLModel uses the Root * Mean Square Error (RMSE) technique to measure performance. RMSE * measures the difference between predicted and actual values for a * single variable. *

              *
            • *
            • *

              * MulticlassAvgFScore: A multiclass MLModel uses the F1 * score technique to measure performance. *

              *
            • *
            *

            * For more information about performance metrics, please see the Amazon * Machine Learning Developer Guide. * @return Returns a reference to this object so that method calls can be * chained together. */ public Evaluation withPerformanceMetrics( PerformanceMetrics performanceMetrics) { setPerformanceMetrics(performanceMetrics); return this; } /** *

            * A description of the most recent details about evaluating the * MLModel. *

            * * @param message * A description of the most recent details about evaluating the * MLModel. */ public void setMessage(String message) { this.message = message; } /** *

            * A description of the most recent details about evaluating the * MLModel. *

            * * @return A description of the most recent details about evaluating the * MLModel. */ public String getMessage() { return this.message; } /** *

            * A description of the most recent details about evaluating the * MLModel. *

            * * @param message * A description of the most recent details about evaluating the * MLModel. * @return Returns a reference to this object so that method calls can be * chained together. */ public Evaluation withMessage(String message) { setMessage(message); return this; } /** * Returns a string representation of this object; useful for testing and * debugging. * * @return A string representation of this object. * * @see java.lang.Object#toString() */ @Override public String toString() { StringBuilder sb = new StringBuilder(); sb.append("{"); if (getEvaluationId() != null) sb.append("EvaluationId: " + getEvaluationId() + ","); if (getMLModelId() != null) sb.append("MLModelId: " + getMLModelId() + ","); if (getEvaluationDataSourceId() != null) sb.append("EvaluationDataSourceId: " + getEvaluationDataSourceId() + ","); if (getInputDataLocationS3() != null) sb.append("InputDataLocationS3: " + getInputDataLocationS3() + ","); if (getCreatedByIamUser() != null) sb.append("CreatedByIamUser: " + getCreatedByIamUser() + ","); if (getCreatedAt() != null) sb.append("CreatedAt: " + getCreatedAt() + ","); if (getLastUpdatedAt() != null) sb.append("LastUpdatedAt: " + getLastUpdatedAt() + ","); if (getName() != null) sb.append("Name: " + getName() + ","); if (getStatus() != null) sb.append("Status: " + getStatus() + ","); if (getPerformanceMetrics() != null) sb.append("PerformanceMetrics: " + getPerformanceMetrics() + ","); if (getMessage() != null) sb.append("Message: " + getMessage()); sb.append("}"); return sb.toString(); } @Override public boolean equals(Object obj) { if (this == obj) return true; if (obj == null) return false; if (obj instanceof Evaluation == false) return false; Evaluation other = (Evaluation) obj; if (other.getEvaluationId() == null ^ this.getEvaluationId() == null) return false; if (other.getEvaluationId() != null && other.getEvaluationId().equals(this.getEvaluationId()) == false) return false; if (other.getMLModelId() == null ^ this.getMLModelId() == null) return false; if (other.getMLModelId() != null && other.getMLModelId().equals(this.getMLModelId()) == false) return false; if (other.getEvaluationDataSourceId() == null ^ this.getEvaluationDataSourceId() == null) return false; if (other.getEvaluationDataSourceId() != null && other.getEvaluationDataSourceId().equals( this.getEvaluationDataSourceId()) == false) return false; if (other.getInputDataLocationS3() == null ^ this.getInputDataLocationS3() == null) return false; if (other.getInputDataLocationS3() != null && other.getInputDataLocationS3().equals( this.getInputDataLocationS3()) == false) return false; if (other.getCreatedByIamUser() == null ^ this.getCreatedByIamUser() == null) return false; if (other.getCreatedByIamUser() != null && other.getCreatedByIamUser().equals( this.getCreatedByIamUser()) == false) return false; if (other.getCreatedAt() == null ^ this.getCreatedAt() == null) return false; if (other.getCreatedAt() != null && other.getCreatedAt().equals(this.getCreatedAt()) == false) return false; if (other.getLastUpdatedAt() == null ^ this.getLastUpdatedAt() == null) return false; if (other.getLastUpdatedAt() != null && other.getLastUpdatedAt().equals(this.getLastUpdatedAt()) == false) return false; if (other.getName() == null ^ this.getName() == null) return false; if (other.getName() != null && other.getName().equals(this.getName()) == false) return false; if (other.getStatus() == null ^ this.getStatus() == null) return false; if (other.getStatus() != null && other.getStatus().equals(this.getStatus()) == false) return false; if (other.getPerformanceMetrics() == null ^ this.getPerformanceMetrics() == null) return false; if (other.getPerformanceMetrics() != null && other.getPerformanceMetrics().equals( this.getPerformanceMetrics()) == false) return false; if (other.getMessage() == null ^ this.getMessage() == null) return false; if (other.getMessage() != null && other.getMessage().equals(this.getMessage()) == false) return false; return true; } @Override public int hashCode() { final int prime = 31; int hashCode = 1; hashCode = prime * hashCode + ((getEvaluationId() == null) ? 0 : getEvaluationId() .hashCode()); hashCode = prime * hashCode + ((getMLModelId() == null) ? 0 : getMLModelId().hashCode()); hashCode = prime * hashCode + ((getEvaluationDataSourceId() == null) ? 0 : getEvaluationDataSourceId().hashCode()); hashCode = prime * hashCode + ((getInputDataLocationS3() == null) ? 0 : getInputDataLocationS3().hashCode()); hashCode = prime * hashCode + ((getCreatedByIamUser() == null) ? 0 : getCreatedByIamUser() .hashCode()); hashCode = prime * hashCode + ((getCreatedAt() == null) ? 0 : getCreatedAt().hashCode()); hashCode = prime * hashCode + ((getLastUpdatedAt() == null) ? 0 : getLastUpdatedAt() .hashCode()); hashCode = prime * hashCode + ((getName() == null) ? 0 : getName().hashCode()); hashCode = prime * hashCode + ((getStatus() == null) ? 0 : getStatus().hashCode()); hashCode = prime * hashCode + ((getPerformanceMetrics() == null) ? 0 : getPerformanceMetrics().hashCode()); hashCode = prime * hashCode + ((getMessage() == null) ? 0 : getMessage().hashCode()); return hashCode; } @Override public Evaluation clone() { try { return (Evaluation) super.clone(); } catch (CloneNotSupportedException e) { throw new IllegalStateException( "Got a CloneNotSupportedException from Object.clone() " + "even though we're Cloneable!", e); } } }




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