/*
 * 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 channel is a named input source that training algorithms can consume. The validation
    /// dataset size is limited to less than 2 GB. The training dataset size must be less
    /// than 100 GB. For more information, see <a href="https://docs.aws.amazon.com/sagemaker/latest/APIReference/API_Channel.html">
    /// Channel</a>.
    /// 
    ///  <note> 
    /// <para>
    /// A validation dataset must contain the same headers as the training dataset.
    /// </para>
    ///  </note>
    /// </summary>
    public partial class AutoMLChannel
    {
        private AutoMLChannelType _channelType;
        private CompressionType _compressionType;
        private string _contentType;
        private AutoMLDataSource _dataSource;
        private string _sampleWeightAttributeName;
        private string _targetAttributeName;

        /// <summary>
        /// Gets and sets the property ChannelType. 
        /// <para>
        /// The channel type (optional) is an <code>enum</code> string. The default value is <code>training</code>.
        /// Channels for training and validation must share the same <code>ContentType</code>
        /// and <code>TargetAttributeName</code>. For information on specifying training and validation
        /// channel types, see <a href="https://docs.aws.amazon.com/sagemaker/latest/dg/autopilot-datasets-problem-types.html#autopilot-data-sources-training-or-validation">How
        /// to specify training and validation datasets</a>.
        /// </para>
        /// </summary>
        public AutoMLChannelType ChannelType
        {
            get { return this._channelType; }
            set { this._channelType = value; }
        }

        // Check to see if ChannelType property is set
        internal bool IsSetChannelType()
        {
            return this._channelType != null;
        }

        /// <summary>
        /// Gets and sets the property CompressionType. 
        /// <para>
        /// You can use <code>Gzip</code> or <code>None</code>. The default value is <code>None</code>.
        /// </para>
        /// </summary>
        public CompressionType CompressionType
        {
            get { return this._compressionType; }
            set { this._compressionType = value; }
        }

        // Check to see if CompressionType property is set
        internal bool IsSetCompressionType()
        {
            return this._compressionType != null;
        }

        /// <summary>
        /// Gets and sets the property ContentType. 
        /// <para>
        /// The content type of the data from the input source. You can use <code>text/csv;header=present</code>
        /// or <code>x-application/vnd.amazon+parquet</code>. The default value is <code>text/csv;header=present</code>.
        /// </para>
        /// </summary>
        [AWSProperty(Max=256)]
        public string ContentType
        {
            get { return this._contentType; }
            set { this._contentType = value; }
        }

        // Check to see if ContentType property is set
        internal bool IsSetContentType()
        {
            return this._contentType != null;
        }

        /// <summary>
        /// Gets and sets the property DataSource. 
        /// <para>
        /// The data source for an AutoML channel.
        /// </para>
        /// </summary>
        [AWSProperty(Required=true)]
        public AutoMLDataSource DataSource
        {
            get { return this._dataSource; }
            set { this._dataSource = value; }
        }

        // Check to see if DataSource property is set
        internal bool IsSetDataSource()
        {
            return this._dataSource != null;
        }

        /// <summary>
        /// Gets and sets the property SampleWeightAttributeName. 
        /// <para>
        /// If specified, this column name indicates which column of the dataset should be treated
        /// as sample weights for use by the objective metric during the training, evaluation,
        /// and the selection of the best model. This column is not considered as a predictive
        /// feature. For more information on Autopilot metrics, see <a href="https://docs.aws.amazon.com/sagemaker/latest/dg/autopilot-metrics-validation.html">Metrics
        /// and validation</a>.
        /// </para>
        ///  
        /// <para>
        /// Sample weights should be numeric, non-negative, with larger values indicating which
        /// rows are more important than others. Data points that have invalid or no weight value
        /// are excluded.
        /// </para>
        ///  
        /// <para>
        /// Support for sample weights is available in <a href="https://docs.aws.amazon.com/sagemaker/latest/APIReference/API_AutoMLAlgorithmConfig.html">Ensembling</a>
        /// mode only.
        /// </para>
        /// </summary>
        [AWSProperty(Min=1, Max=256)]
        public string SampleWeightAttributeName
        {
            get { return this._sampleWeightAttributeName; }
            set { this._sampleWeightAttributeName = value; }
        }

        // Check to see if SampleWeightAttributeName property is set
        internal bool IsSetSampleWeightAttributeName()
        {
            return this._sampleWeightAttributeName != null;
        }

        /// <summary>
        /// Gets and sets the property TargetAttributeName. 
        /// <para>
        /// The name of the target variable in supervised learning, usually represented by 'y'.
        /// </para>
        /// </summary>
        [AWSProperty(Required=true, Min=1)]
        public string TargetAttributeName
        {
            get { return this._targetAttributeName; }
            set { this._targetAttributeName = value; }
        }

        // Check to see if TargetAttributeName property is set
        internal bool IsSetTargetAttributeName()
        {
            return this._targetAttributeName != null;
        }

    }
}