/*
 * 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 sagemaker-2017-07-24.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.SageMaker.Model
{
    /// <summary>
    /// A collection of settings used for an AutoML job.
    /// </summary>
    public partial class AutoMLJobConfig
    {
        private AutoMLCandidateGenerationConfig _candidateGenerationConfig;
        private AutoMLJobCompletionCriteria _completionCriteria;
        private AutoMLDataSplitConfig _dataSplitConfig;
        private AutoMLMode _mode;
        private AutoMLSecurityConfig _securityConfig;

        /// <summary>
        /// Gets and sets the property CandidateGenerationConfig. 
        /// <para>
        /// The configuration for generating a candidate for an AutoML job (optional). 
        /// </para>
        /// </summary>
        public AutoMLCandidateGenerationConfig CandidateGenerationConfig
        {
            get { return this._candidateGenerationConfig; }
            set { this._candidateGenerationConfig = value; }
        }

        // Check to see if CandidateGenerationConfig property is set
        internal bool IsSetCandidateGenerationConfig()
        {
            return this._candidateGenerationConfig != null;
        }

        /// <summary>
        /// Gets and sets the property CompletionCriteria. 
        /// <para>
        /// How long an AutoML job is allowed to run, or how many candidates a job is allowed
        /// to generate.
        /// </para>
        /// </summary>
        public AutoMLJobCompletionCriteria CompletionCriteria
        {
            get { return this._completionCriteria; }
            set { this._completionCriteria = value; }
        }

        // Check to see if CompletionCriteria property is set
        internal bool IsSetCompletionCriteria()
        {
            return this._completionCriteria != null;
        }

        /// <summary>
        /// Gets and sets the property DataSplitConfig. 
        /// <para>
        /// The configuration for splitting the input training dataset.
        /// </para>
        ///  
        /// <para>
        /// Type: AutoMLDataSplitConfig
        /// </para>
        /// </summary>
        public AutoMLDataSplitConfig DataSplitConfig
        {
            get { return this._dataSplitConfig; }
            set { this._dataSplitConfig = value; }
        }

        // Check to see if DataSplitConfig property is set
        internal bool IsSetDataSplitConfig()
        {
            return this._dataSplitConfig != null;
        }

        /// <summary>
        /// Gets and sets the property Mode. 
        /// <para>
        /// The method that Autopilot uses to train the data. You can either specify the mode
        /// manually or let Autopilot choose for you based on the dataset size by selecting <code>AUTO</code>.
        /// In <code>AUTO</code> mode, Autopilot chooses <code>ENSEMBLING</code> for datasets
        /// smaller than 100 MB, and <code>HYPERPARAMETER_TUNING</code> for larger ones.
        /// </para>
        ///  
        /// <para>
        /// The <code>ENSEMBLING</code> mode uses a multi-stack ensemble model to predict classification
        /// and regression tasks directly from your dataset. This machine learning mode combines
        /// several base models to produce an optimal predictive model. It then uses a stacking
        /// ensemble method to combine predictions from contributing members. A multi-stack ensemble
        /// model can provide better performance over a single model by combining the predictive
        /// capabilities of multiple models. See <a href="https://docs.aws.amazon.com/sagemaker/latest/dg/autopilot-model-support-validation.html#autopilot-algorithm-support">Autopilot
        /// algorithm support</a> for a list of algorithms supported by <code>ENSEMBLING</code>
        /// mode.
        /// </para>
        ///  
        /// <para>
        /// The <code>HYPERPARAMETER_TUNING</code> (HPO) mode uses the best hyperparameters to
        /// train the best version of a model. HPO automatically selects an algorithm for the
        /// type of problem you want to solve. Then HPO finds the best hyperparameters according
        /// to your objective metric. See <a href="https://docs.aws.amazon.com/sagemaker/latest/dg/autopilot-model-support-validation.html#autopilot-algorithm-support">Autopilot
        /// algorithm support</a> for a list of algorithms supported by <code>HYPERPARAMETER_TUNING</code>
        /// mode.
        /// </para>
        /// </summary>
        public AutoMLMode Mode
        {
            get { return this._mode; }
            set { this._mode = value; }
        }

        // Check to see if Mode property is set
        internal bool IsSetMode()
        {
            return this._mode != null;
        }

        /// <summary>
        /// Gets and sets the property SecurityConfig. 
        /// <para>
        /// The security configuration for traffic encryption or Amazon VPC settings.
        /// </para>
        /// </summary>
        public AutoMLSecurityConfig SecurityConfig
        {
            get { return this._securityConfig; }
            set { this._securityConfig = value; }
        }

        // Check to see if SecurityConfig property is set
        internal bool IsSetSecurityConfig()
        {
            return this._securityConfig != null;
        }

    }
}