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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.frauddetector.model;
import java.io.Serializable;
import javax.annotation.Generated;
import com.amazonaws.protocol.StructuredPojo;
import com.amazonaws.protocol.ProtocolMarshaller;
/**
*
* The prediction explanations that provide insight into how each event variable impacted the model version's fraud
* prediction score.
*
*
* @see AWS API Documentation
*/
@Generated("com.amazonaws:aws-java-sdk-code-generator")
public class PredictionExplanations implements Serializable, Cloneable, StructuredPojo {
/**
*
* The details of the event variable's impact on the prediction score.
*
*/
private java.util.List variableImpactExplanations;
/**
*
* The details of the aggregated variables impact on the prediction score.
*
*
* Account Takeover Insights (ATI) model uses event variables from the login data you provide to continuously
* calculate a set of variables (aggregated variables) based on historical events. For example, your ATI model might
* calculate the number of times an user has logged in using the same IP address. In this case, event variables used
* to derive the aggregated variables are IP address and user.
*
*/
private java.util.List aggregatedVariablesImpactExplanations;
/**
*
* The details of the event variable's impact on the prediction score.
*
*
* @return The details of the event variable's impact on the prediction score.
*/
public java.util.List getVariableImpactExplanations() {
return variableImpactExplanations;
}
/**
*
* The details of the event variable's impact on the prediction score.
*
*
* @param variableImpactExplanations
* The details of the event variable's impact on the prediction score.
*/
public void setVariableImpactExplanations(java.util.Collection variableImpactExplanations) {
if (variableImpactExplanations == null) {
this.variableImpactExplanations = null;
return;
}
this.variableImpactExplanations = new java.util.ArrayList(variableImpactExplanations);
}
/**
*
* The details of the event variable's impact on the prediction score.
*
*
* NOTE: This method appends the values to the existing list (if any). Use
* {@link #setVariableImpactExplanations(java.util.Collection)} or
* {@link #withVariableImpactExplanations(java.util.Collection)} if you want to override the existing values.
*
*
* @param variableImpactExplanations
* The details of the event variable's impact on the prediction score.
* @return Returns a reference to this object so that method calls can be chained together.
*/
public PredictionExplanations withVariableImpactExplanations(VariableImpactExplanation... variableImpactExplanations) {
if (this.variableImpactExplanations == null) {
setVariableImpactExplanations(new java.util.ArrayList(variableImpactExplanations.length));
}
for (VariableImpactExplanation ele : variableImpactExplanations) {
this.variableImpactExplanations.add(ele);
}
return this;
}
/**
*
* The details of the event variable's impact on the prediction score.
*
*
* @param variableImpactExplanations
* The details of the event variable's impact on the prediction score.
* @return Returns a reference to this object so that method calls can be chained together.
*/
public PredictionExplanations withVariableImpactExplanations(java.util.Collection variableImpactExplanations) {
setVariableImpactExplanations(variableImpactExplanations);
return this;
}
/**
*
* The details of the aggregated variables impact on the prediction score.
*
*
* Account Takeover Insights (ATI) model uses event variables from the login data you provide to continuously
* calculate a set of variables (aggregated variables) based on historical events. For example, your ATI model might
* calculate the number of times an user has logged in using the same IP address. In this case, event variables used
* to derive the aggregated variables are IP address and user.
*
*
* @return The details of the aggregated variables impact on the prediction score.
*
* Account Takeover Insights (ATI) model uses event variables from the login data you provide to
* continuously calculate a set of variables (aggregated variables) based on historical events. For example,
* your ATI model might calculate the number of times an user has logged in using the same IP address. In
* this case, event variables used to derive the aggregated variables are IP address and
* user.
*/
public java.util.List getAggregatedVariablesImpactExplanations() {
return aggregatedVariablesImpactExplanations;
}
/**
*
* The details of the aggregated variables impact on the prediction score.
*
*
* Account Takeover Insights (ATI) model uses event variables from the login data you provide to continuously
* calculate a set of variables (aggregated variables) based on historical events. For example, your ATI model might
* calculate the number of times an user has logged in using the same IP address. In this case, event variables used
* to derive the aggregated variables are IP address and user.
*
*
* @param aggregatedVariablesImpactExplanations
* The details of the aggregated variables impact on the prediction score.
*
* Account Takeover Insights (ATI) model uses event variables from the login data you provide to continuously
* calculate a set of variables (aggregated variables) based on historical events. For example, your ATI
* model might calculate the number of times an user has logged in using the same IP address. In this case,
* event variables used to derive the aggregated variables are IP address and user.
*/
public void setAggregatedVariablesImpactExplanations(java.util.Collection aggregatedVariablesImpactExplanations) {
if (aggregatedVariablesImpactExplanations == null) {
this.aggregatedVariablesImpactExplanations = null;
return;
}
this.aggregatedVariablesImpactExplanations = new java.util.ArrayList(aggregatedVariablesImpactExplanations);
}
/**
*
* The details of the aggregated variables impact on the prediction score.
*
*
* Account Takeover Insights (ATI) model uses event variables from the login data you provide to continuously
* calculate a set of variables (aggregated variables) based on historical events. For example, your ATI model might
* calculate the number of times an user has logged in using the same IP address. In this case, event variables used
* to derive the aggregated variables are IP address and user.
*
*
* NOTE: This method appends the values to the existing list (if any). Use
* {@link #setAggregatedVariablesImpactExplanations(java.util.Collection)} or
* {@link #withAggregatedVariablesImpactExplanations(java.util.Collection)} if you want to override the existing
* values.
*
*
* @param aggregatedVariablesImpactExplanations
* The details of the aggregated variables impact on the prediction score.
*
* Account Takeover Insights (ATI) model uses event variables from the login data you provide to continuously
* calculate a set of variables (aggregated variables) based on historical events. For example, your ATI
* model might calculate the number of times an user has logged in using the same IP address. In this case,
* event variables used to derive the aggregated variables are IP address and user.
* @return Returns a reference to this object so that method calls can be chained together.
*/
public PredictionExplanations withAggregatedVariablesImpactExplanations(AggregatedVariablesImpactExplanation... aggregatedVariablesImpactExplanations) {
if (this.aggregatedVariablesImpactExplanations == null) {
setAggregatedVariablesImpactExplanations(new java.util.ArrayList(aggregatedVariablesImpactExplanations.length));
}
for (AggregatedVariablesImpactExplanation ele : aggregatedVariablesImpactExplanations) {
this.aggregatedVariablesImpactExplanations.add(ele);
}
return this;
}
/**
*
* The details of the aggregated variables impact on the prediction score.
*
*
* Account Takeover Insights (ATI) model uses event variables from the login data you provide to continuously
* calculate a set of variables (aggregated variables) based on historical events. For example, your ATI model might
* calculate the number of times an user has logged in using the same IP address. In this case, event variables used
* to derive the aggregated variables are IP address and user.
*
*
* @param aggregatedVariablesImpactExplanations
* The details of the aggregated variables impact on the prediction score.
*
* Account Takeover Insights (ATI) model uses event variables from the login data you provide to continuously
* calculate a set of variables (aggregated variables) based on historical events. For example, your ATI
* model might calculate the number of times an user has logged in using the same IP address. In this case,
* event variables used to derive the aggregated variables are IP address and user.
* @return Returns a reference to this object so that method calls can be chained together.
*/
public PredictionExplanations withAggregatedVariablesImpactExplanations(
java.util.Collection aggregatedVariablesImpactExplanations) {
setAggregatedVariablesImpactExplanations(aggregatedVariablesImpactExplanations);
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 (getVariableImpactExplanations() != null)
sb.append("VariableImpactExplanations: ").append(getVariableImpactExplanations()).append(",");
if (getAggregatedVariablesImpactExplanations() != null)
sb.append("AggregatedVariablesImpactExplanations: ").append(getAggregatedVariablesImpactExplanations());
sb.append("}");
return sb.toString();
}
@Override
public boolean equals(Object obj) {
if (this == obj)
return true;
if (obj == null)
return false;
if (obj instanceof PredictionExplanations == false)
return false;
PredictionExplanations other = (PredictionExplanations) obj;
if (other.getVariableImpactExplanations() == null ^ this.getVariableImpactExplanations() == null)
return false;
if (other.getVariableImpactExplanations() != null && other.getVariableImpactExplanations().equals(this.getVariableImpactExplanations()) == false)
return false;
if (other.getAggregatedVariablesImpactExplanations() == null ^ this.getAggregatedVariablesImpactExplanations() == null)
return false;
if (other.getAggregatedVariablesImpactExplanations() != null
&& other.getAggregatedVariablesImpactExplanations().equals(this.getAggregatedVariablesImpactExplanations()) == false)
return false;
return true;
}
@Override
public int hashCode() {
final int prime = 31;
int hashCode = 1;
hashCode = prime * hashCode + ((getVariableImpactExplanations() == null) ? 0 : getVariableImpactExplanations().hashCode());
hashCode = prime * hashCode + ((getAggregatedVariablesImpactExplanations() == null) ? 0 : getAggregatedVariablesImpactExplanations().hashCode());
return hashCode;
}
@Override
public PredictionExplanations clone() {
try {
return (PredictionExplanations) 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.frauddetector.model.transform.PredictionExplanationsMarshaller.getInstance().marshall(this, protocolMarshaller);
}
}