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/*
 * Copyright 2019-2024 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.forecast.model;

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

/**
 * 

* Provides information about the method that featurizes (transforms) a dataset field. The method is part of the * FeaturizationPipeline of the Featurization object. *

*

* The following is an example of how you specify a FeaturizationMethod object. *

*

* { *

*

* "FeaturizationMethodName": "filling", *

*

* "FeaturizationMethodParameters": {"aggregation": "sum", "middlefill": "zero", "backfill": "zero"} *

*

* } *

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

* The name of the method. The "filling" method is the only supported method. *

*/ private String featurizationMethodName; /** *

* The method parameters (key-value pairs), which are a map of override parameters. Specify these parameters to * override the default values. Related Time Series attributes do not accept aggregation parameters. *

*

* The following list shows the parameters and their valid values for the "filling" featurization method for a * Target Time Series dataset. Bold signifies the default value. *

*
    *
  • *

    * aggregation: sum, avg, first, min, max *

    *
  • *
  • *

    * frontfill: none *

    *
  • *
  • *

    * middlefill: zero, nan (not a number), value, median, * mean, min, max *

    *
  • *
  • *

    * backfill: zero, nan, value, median, mean, * min, max *

    *
  • *
*

* The following list shows the parameters and their valid values for a Related Time Series featurization * method (there are no defaults): *

*
    *
  • *

    * middlefill: zero, value, median, mean, * min, max *

    *
  • *
  • *

    * backfill: zero, value, median, mean, * min, max *

    *
  • *
  • *

    * futurefill: zero, value, median, mean, * min, max *

    *
  • *
*

* To set a filling method to a specific value, set the fill parameter to value and define the value in * a corresponding _value parameter. For example, to set backfilling to a value of 2, include the * following: "backfill": "value" and "backfill_value":"2". *

*/ private java.util.Map featurizationMethodParameters; /** *

* The name of the method. The "filling" method is the only supported method. *

* * @param featurizationMethodName * The name of the method. The "filling" method is the only supported method. * @see FeaturizationMethodName */ public void setFeaturizationMethodName(String featurizationMethodName) { this.featurizationMethodName = featurizationMethodName; } /** *

* The name of the method. The "filling" method is the only supported method. *

* * @return The name of the method. The "filling" method is the only supported method. * @see FeaturizationMethodName */ public String getFeaturizationMethodName() { return this.featurizationMethodName; } /** *

* The name of the method. The "filling" method is the only supported method. *

* * @param featurizationMethodName * The name of the method. The "filling" method is the only supported method. * @return Returns a reference to this object so that method calls can be chained together. * @see FeaturizationMethodName */ public FeaturizationMethod withFeaturizationMethodName(String featurizationMethodName) { setFeaturizationMethodName(featurizationMethodName); return this; } /** *

* The name of the method. The "filling" method is the only supported method. *

* * @param featurizationMethodName * The name of the method. The "filling" method is the only supported method. * @return Returns a reference to this object so that method calls can be chained together. * @see FeaturizationMethodName */ public FeaturizationMethod withFeaturizationMethodName(FeaturizationMethodName featurizationMethodName) { this.featurizationMethodName = featurizationMethodName.toString(); return this; } /** *

* The method parameters (key-value pairs), which are a map of override parameters. Specify these parameters to * override the default values. Related Time Series attributes do not accept aggregation parameters. *

*

* The following list shows the parameters and their valid values for the "filling" featurization method for a * Target Time Series dataset. Bold signifies the default value. *

*
    *
  • *

    * aggregation: sum, avg, first, min, max *

    *
  • *
  • *

    * frontfill: none *

    *
  • *
  • *

    * middlefill: zero, nan (not a number), value, median, * mean, min, max *

    *
  • *
  • *

    * backfill: zero, nan, value, median, mean, * min, max *

    *
  • *
*

* The following list shows the parameters and their valid values for a Related Time Series featurization * method (there are no defaults): *

*
    *
  • *

    * middlefill: zero, value, median, mean, * min, max *

    *
  • *
  • *

    * backfill: zero, value, median, mean, * min, max *

    *
  • *
  • *

    * futurefill: zero, value, median, mean, * min, max *

    *
  • *
*

* To set a filling method to a specific value, set the fill parameter to value and define the value in * a corresponding _value parameter. For example, to set backfilling to a value of 2, include the * following: "backfill": "value" and "backfill_value":"2". *

* * @return The method parameters (key-value pairs), which are a map of override parameters. Specify these parameters * to override the default values. Related Time Series attributes do not accept aggregation parameters.

*

* The following list shows the parameters and their valid values for the "filling" featurization method for * a Target Time Series dataset. Bold signifies the default value. *

*
    *
  • *

    * aggregation: sum, avg, first, min, * max *

    *
  • *
  • *

    * frontfill: none *

    *
  • *
  • *

    * middlefill: zero, nan (not a number), value, * median, mean, min, max *

    *
  • *
  • *

    * backfill: zero, nan, value, median, * mean, min, max *

    *
  • *
*

* The following list shows the parameters and their valid values for a Related Time Series * featurization method (there are no defaults): *

*
    *
  • *

    * middlefill: zero, value, median, mean, * min, max *

    *
  • *
  • *

    * backfill: zero, value, median, mean, * min, max *

    *
  • *
  • *

    * futurefill: zero, value, median, mean, * min, max *

    *
  • *
*

* To set a filling method to a specific value, set the fill parameter to value and define the * value in a corresponding _value parameter. For example, to set backfilling to a value of 2, * include the following: "backfill": "value" and "backfill_value":"2". */ public java.util.Map getFeaturizationMethodParameters() { return featurizationMethodParameters; } /** *

* The method parameters (key-value pairs), which are a map of override parameters. Specify these parameters to * override the default values. Related Time Series attributes do not accept aggregation parameters. *

*

* The following list shows the parameters and their valid values for the "filling" featurization method for a * Target Time Series dataset. Bold signifies the default value. *

*
    *
  • *

    * aggregation: sum, avg, first, min, max *

    *
  • *
  • *

    * frontfill: none *

    *
  • *
  • *

    * middlefill: zero, nan (not a number), value, median, * mean, min, max *

    *
  • *
  • *

    * backfill: zero, nan, value, median, mean, * min, max *

    *
  • *
*

* The following list shows the parameters and their valid values for a Related Time Series featurization * method (there are no defaults): *

*
    *
  • *

    * middlefill: zero, value, median, mean, * min, max *

    *
  • *
  • *

    * backfill: zero, value, median, mean, * min, max *

    *
  • *
  • *

    * futurefill: zero, value, median, mean, * min, max *

    *
  • *
*

* To set a filling method to a specific value, set the fill parameter to value and define the value in * a corresponding _value parameter. For example, to set backfilling to a value of 2, include the * following: "backfill": "value" and "backfill_value":"2". *

* * @param featurizationMethodParameters * The method parameters (key-value pairs), which are a map of override parameters. Specify these parameters * to override the default values. Related Time Series attributes do not accept aggregation parameters.

*

* The following list shows the parameters and their valid values for the "filling" featurization method for * a Target Time Series dataset. Bold signifies the default value. *

*
    *
  • *

    * aggregation: sum, avg, first, min, * max *

    *
  • *
  • *

    * frontfill: none *

    *
  • *
  • *

    * middlefill: zero, nan (not a number), value, * median, mean, min, max *

    *
  • *
  • *

    * backfill: zero, nan, value, median, * mean, min, max *

    *
  • *
*

* The following list shows the parameters and their valid values for a Related Time Series * featurization method (there are no defaults): *

*
    *
  • *

    * middlefill: zero, value, median, mean, * min, max *

    *
  • *
  • *

    * backfill: zero, value, median, mean, * min, max *

    *
  • *
  • *

    * futurefill: zero, value, median, mean, * min, max *

    *
  • *
*

* To set a filling method to a specific value, set the fill parameter to value and define the * value in a corresponding _value parameter. For example, to set backfilling to a value of 2, * include the following: "backfill": "value" and "backfill_value":"2". */ public void setFeaturizationMethodParameters(java.util.Map featurizationMethodParameters) { this.featurizationMethodParameters = featurizationMethodParameters; } /** *

* The method parameters (key-value pairs), which are a map of override parameters. Specify these parameters to * override the default values. Related Time Series attributes do not accept aggregation parameters. *

*

* The following list shows the parameters and their valid values for the "filling" featurization method for a * Target Time Series dataset. Bold signifies the default value. *

*
    *
  • *

    * aggregation: sum, avg, first, min, max *

    *
  • *
  • *

    * frontfill: none *

    *
  • *
  • *

    * middlefill: zero, nan (not a number), value, median, * mean, min, max *

    *
  • *
  • *

    * backfill: zero, nan, value, median, mean, * min, max *

    *
  • *
*

* The following list shows the parameters and their valid values for a Related Time Series featurization * method (there are no defaults): *

*
    *
  • *

    * middlefill: zero, value, median, mean, * min, max *

    *
  • *
  • *

    * backfill: zero, value, median, mean, * min, max *

    *
  • *
  • *

    * futurefill: zero, value, median, mean, * min, max *

    *
  • *
*

* To set a filling method to a specific value, set the fill parameter to value and define the value in * a corresponding _value parameter. For example, to set backfilling to a value of 2, include the * following: "backfill": "value" and "backfill_value":"2". *

* * @param featurizationMethodParameters * The method parameters (key-value pairs), which are a map of override parameters. Specify these parameters * to override the default values. Related Time Series attributes do not accept aggregation parameters.

*

* The following list shows the parameters and their valid values for the "filling" featurization method for * a Target Time Series dataset. Bold signifies the default value. *

*
    *
  • *

    * aggregation: sum, avg, first, min, * max *

    *
  • *
  • *

    * frontfill: none *

    *
  • *
  • *

    * middlefill: zero, nan (not a number), value, * median, mean, min, max *

    *
  • *
  • *

    * backfill: zero, nan, value, median, * mean, min, max *

    *
  • *
*

* The following list shows the parameters and their valid values for a Related Time Series * featurization method (there are no defaults): *

*
    *
  • *

    * middlefill: zero, value, median, mean, * min, max *

    *
  • *
  • *

    * backfill: zero, value, median, mean, * min, max *

    *
  • *
  • *

    * futurefill: zero, value, median, mean, * min, max *

    *
  • *
*

* To set a filling method to a specific value, set the fill parameter to value and define the * value in a corresponding _value parameter. For example, to set backfilling to a value of 2, * include the following: "backfill": "value" and "backfill_value":"2". * @return Returns a reference to this object so that method calls can be chained together. */ public FeaturizationMethod withFeaturizationMethodParameters(java.util.Map featurizationMethodParameters) { setFeaturizationMethodParameters(featurizationMethodParameters); return this; } /** * Add a single FeaturizationMethodParameters entry * * @see FeaturizationMethod#withFeaturizationMethodParameters * @returns a reference to this object so that method calls can be chained together. */ public FeaturizationMethod addFeaturizationMethodParametersEntry(String key, String value) { if (null == this.featurizationMethodParameters) { this.featurizationMethodParameters = new java.util.HashMap(); } if (this.featurizationMethodParameters.containsKey(key)) throw new IllegalArgumentException("Duplicated keys (" + key.toString() + ") are provided."); this.featurizationMethodParameters.put(key, value); return this; } /** * Removes all the entries added into FeaturizationMethodParameters. * * @return Returns a reference to this object so that method calls can be chained together. */ public FeaturizationMethod clearFeaturizationMethodParametersEntries() { this.featurizationMethodParameters = null; 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 (getFeaturizationMethodName() != null) sb.append("FeaturizationMethodName: ").append(getFeaturizationMethodName()).append(","); if (getFeaturizationMethodParameters() != null) sb.append("FeaturizationMethodParameters: ").append(getFeaturizationMethodParameters()); sb.append("}"); return sb.toString(); } @Override public boolean equals(Object obj) { if (this == obj) return true; if (obj == null) return false; if (obj instanceof FeaturizationMethod == false) return false; FeaturizationMethod other = (FeaturizationMethod) obj; if (other.getFeaturizationMethodName() == null ^ this.getFeaturizationMethodName() == null) return false; if (other.getFeaturizationMethodName() != null && other.getFeaturizationMethodName().equals(this.getFeaturizationMethodName()) == false) return false; if (other.getFeaturizationMethodParameters() == null ^ this.getFeaturizationMethodParameters() == null) return false; if (other.getFeaturizationMethodParameters() != null && other.getFeaturizationMethodParameters().equals(this.getFeaturizationMethodParameters()) == false) return false; return true; } @Override public int hashCode() { final int prime = 31; int hashCode = 1; hashCode = prime * hashCode + ((getFeaturizationMethodName() == null) ? 0 : getFeaturizationMethodName().hashCode()); hashCode = prime * hashCode + ((getFeaturizationMethodParameters() == null) ? 0 : getFeaturizationMethodParameters().hashCode()); return hashCode; } @Override public FeaturizationMethod clone() { try { return (FeaturizationMethod) 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.forecast.model.transform.FeaturizationMethodMarshaller.getInstance().marshall(this, protocolMarshaller); } }





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