/* * 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; } } }