/*
* Copyright 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.
*/
/*
* Do not modify this file. This file is generated from the frauddetector-2019-11-15.normal.json service model.
*/
using System;
using System.Collections.Generic;
using System.Xml.Serialization;
using System.Text;
using System.IO;
using System.Net;
using Amazon.Runtime;
using Amazon.Runtime.Internal;
namespace Amazon.FraudDetector.Model
{
///
/// The Account Takeover Insights (ATI) model performance score.
///
public partial class ATIModelPerformance
{
private float? _asi;
///
/// Gets and sets the property Asi.
///
/// The anomaly separation index (ASI) score. This metric summarizes the overall ability
/// of the model to separate anomalous activities from the normal behavior. Depending
/// on the business, a large fraction of these anomalous activities can be malicious and
/// correspond to the account takeover attacks. A model with no separability power will
/// have the lowest possible ASI score of 0.5, whereas the a model with a high separability
/// power will have the highest possible ASI score of 1.0
///
///
public float Asi
{
get { return this._asi.GetValueOrDefault(); }
set { this._asi = value; }
}
// Check to see if Asi property is set
internal bool IsSetAsi()
{
return this._asi.HasValue;
}
}
}