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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 details of the impact of aggregated variables on the prediction score.
*
*
* Account Takeover Insights (ATI) model uses the login data you provide to continuously calculate a set of variables
* (aggregated variables) based on historical events. For example, the 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.
*
*
* @see AWS API Documentation
*/
@Generated("com.amazonaws:aws-java-sdk-code-generator")
public class AggregatedVariablesImpactExplanation implements Serializable, Cloneable, StructuredPojo {
/**
*
* The names of all the event variables that were used to derive the aggregated variables.
*
*/
private java.util.List eventVariableNames;
/**
*
* The relative impact of the aggregated variables in terms of magnitude on the prediction scores.
*
*/
private String relativeImpact;
/**
*
* The raw, uninterpreted value represented as log-odds of the fraud. These values are usually between -10 to +10,
* but range from -infinity to +infinity.
*
*
* -
*
* A positive value indicates that the variables drove the risk score up.
*
*
* -
*
* A negative value indicates that the variables drove the risk score down.
*
*
*
*/
private Float logOddsImpact;
/**
*
* The names of all the event variables that were used to derive the aggregated variables.
*
*
* @return The names of all the event variables that were used to derive the aggregated variables.
*/
public java.util.List getEventVariableNames() {
return eventVariableNames;
}
/**
*
* The names of all the event variables that were used to derive the aggregated variables.
*
*
* @param eventVariableNames
* The names of all the event variables that were used to derive the aggregated variables.
*/
public void setEventVariableNames(java.util.Collection eventVariableNames) {
if (eventVariableNames == null) {
this.eventVariableNames = null;
return;
}
this.eventVariableNames = new java.util.ArrayList(eventVariableNames);
}
/**
*
* The names of all the event variables that were used to derive the aggregated variables.
*
*
* NOTE: This method appends the values to the existing list (if any). Use
* {@link #setEventVariableNames(java.util.Collection)} or {@link #withEventVariableNames(java.util.Collection)} if
* you want to override the existing values.
*
*
* @param eventVariableNames
* The names of all the event variables that were used to derive the aggregated variables.
* @return Returns a reference to this object so that method calls can be chained together.
*/
public AggregatedVariablesImpactExplanation withEventVariableNames(String... eventVariableNames) {
if (this.eventVariableNames == null) {
setEventVariableNames(new java.util.ArrayList(eventVariableNames.length));
}
for (String ele : eventVariableNames) {
this.eventVariableNames.add(ele);
}
return this;
}
/**
*
* The names of all the event variables that were used to derive the aggregated variables.
*
*
* @param eventVariableNames
* The names of all the event variables that were used to derive the aggregated variables.
* @return Returns a reference to this object so that method calls can be chained together.
*/
public AggregatedVariablesImpactExplanation withEventVariableNames(java.util.Collection eventVariableNames) {
setEventVariableNames(eventVariableNames);
return this;
}
/**
*
* The relative impact of the aggregated variables in terms of magnitude on the prediction scores.
*
*
* @param relativeImpact
* The relative impact of the aggregated variables in terms of magnitude on the prediction scores.
*/
public void setRelativeImpact(String relativeImpact) {
this.relativeImpact = relativeImpact;
}
/**
*
* The relative impact of the aggregated variables in terms of magnitude on the prediction scores.
*
*
* @return The relative impact of the aggregated variables in terms of magnitude on the prediction scores.
*/
public String getRelativeImpact() {
return this.relativeImpact;
}
/**
*
* The relative impact of the aggregated variables in terms of magnitude on the prediction scores.
*
*
* @param relativeImpact
* The relative impact of the aggregated variables in terms of magnitude on the prediction scores.
* @return Returns a reference to this object so that method calls can be chained together.
*/
public AggregatedVariablesImpactExplanation withRelativeImpact(String relativeImpact) {
setRelativeImpact(relativeImpact);
return this;
}
/**
*
* The raw, uninterpreted value represented as log-odds of the fraud. These values are usually between -10 to +10,
* but range from -infinity to +infinity.
*
*
* -
*
* A positive value indicates that the variables drove the risk score up.
*
*
* -
*
* A negative value indicates that the variables drove the risk score down.
*
*
*
*
* @param logOddsImpact
* The raw, uninterpreted value represented as log-odds of the fraud. These values are usually between -10 to
* +10, but range from -infinity to +infinity.
*
* -
*
* A positive value indicates that the variables drove the risk score up.
*
*
* -
*
* A negative value indicates that the variables drove the risk score down.
*
*
*/
public void setLogOddsImpact(Float logOddsImpact) {
this.logOddsImpact = logOddsImpact;
}
/**
*
* The raw, uninterpreted value represented as log-odds of the fraud. These values are usually between -10 to +10,
* but range from -infinity to +infinity.
*
*
* -
*
* A positive value indicates that the variables drove the risk score up.
*
*
* -
*
* A negative value indicates that the variables drove the risk score down.
*
*
*
*
* @return The raw, uninterpreted value represented as log-odds of the fraud. These values are usually between -10
* to +10, but range from -infinity to +infinity.
*
* -
*
* A positive value indicates that the variables drove the risk score up.
*
*
* -
*
* A negative value indicates that the variables drove the risk score down.
*
*
*/
public Float getLogOddsImpact() {
return this.logOddsImpact;
}
/**
*
* The raw, uninterpreted value represented as log-odds of the fraud. These values are usually between -10 to +10,
* but range from -infinity to +infinity.
*
*
* -
*
* A positive value indicates that the variables drove the risk score up.
*
*
* -
*
* A negative value indicates that the variables drove the risk score down.
*
*
*
*
* @param logOddsImpact
* The raw, uninterpreted value represented as log-odds of the fraud. These values are usually between -10 to
* +10, but range from -infinity to +infinity.
*
* -
*
* A positive value indicates that the variables drove the risk score up.
*
*
* -
*
* A negative value indicates that the variables drove the risk score down.
*
*
* @return Returns a reference to this object so that method calls can be chained together.
*/
public AggregatedVariablesImpactExplanation withLogOddsImpact(Float logOddsImpact) {
setLogOddsImpact(logOddsImpact);
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 (getEventVariableNames() != null)
sb.append("EventVariableNames: ").append(getEventVariableNames()).append(",");
if (getRelativeImpact() != null)
sb.append("RelativeImpact: ").append(getRelativeImpact()).append(",");
if (getLogOddsImpact() != null)
sb.append("LogOddsImpact: ").append(getLogOddsImpact());
sb.append("}");
return sb.toString();
}
@Override
public boolean equals(Object obj) {
if (this == obj)
return true;
if (obj == null)
return false;
if (obj instanceof AggregatedVariablesImpactExplanation == false)
return false;
AggregatedVariablesImpactExplanation other = (AggregatedVariablesImpactExplanation) obj;
if (other.getEventVariableNames() == null ^ this.getEventVariableNames() == null)
return false;
if (other.getEventVariableNames() != null && other.getEventVariableNames().equals(this.getEventVariableNames()) == false)
return false;
if (other.getRelativeImpact() == null ^ this.getRelativeImpact() == null)
return false;
if (other.getRelativeImpact() != null && other.getRelativeImpact().equals(this.getRelativeImpact()) == false)
return false;
if (other.getLogOddsImpact() == null ^ this.getLogOddsImpact() == null)
return false;
if (other.getLogOddsImpact() != null && other.getLogOddsImpact().equals(this.getLogOddsImpact()) == false)
return false;
return true;
}
@Override
public int hashCode() {
final int prime = 31;
int hashCode = 1;
hashCode = prime * hashCode + ((getEventVariableNames() == null) ? 0 : getEventVariableNames().hashCode());
hashCode = prime * hashCode + ((getRelativeImpact() == null) ? 0 : getRelativeImpact().hashCode());
hashCode = prime * hashCode + ((getLogOddsImpact() == null) ? 0 : getLogOddsImpact().hashCode());
return hashCode;
}
@Override
public AggregatedVariablesImpactExplanation clone() {
try {
return (AggregatedVariablesImpactExplanation) 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.AggregatedVariablesImpactExplanationMarshaller.getInstance().marshall(this, protocolMarshaller);
}
}