DataOperationsCatalog.ShuffleRows 方法

定义

命名空间:

Microsoft.ML

程序集:

Microsoft.ML.Data.dll

包:

Microsoft.ML v3.0.1

对行 input进行随机排列。

public Microsoft.ML.IDataView ShuffleRows (Microsoft.ML.IDataView input, int? seed = default, int shufflePoolSize = 1000, bool shuffleSource = true);

member this.ShuffleRows : Microsoft.ML.IDataView * Nullable<int> * int * bool -> Microsoft.ML.IDataView

Public Function ShuffleRows (input As IDataView, Optional seed As Nullable(Of Integer) = Nothing, Optional shufflePoolSize As Integer = 1000, Optional shuffleSource As Boolean = true) As IDataView

参数

input

IDataView

输入数据。

seed

Nullable<Int32>

随机种子。 如果未指定，则随机状态将改为派生自 MLContext该状态。

shufflePoolSize

Int32

要保存在池中的行数。 将此设置设置为 1 会关闭池混排， ShuffleRows(IDataView, Nullable<Int32>, Int32, Boolean) 并且仅按随机顺序读取 input 来执行随机排列。

shuffleSource

Boolean

如果 false，转换不会尝试按随机顺序读取，并且只使用池来随机读取 input 。 如果属性为 inputfalse.，CanShuffle则此参数无效。

返回

IDataView

示例

using System;
using System.Collections.Generic;
using Microsoft.ML;

namespace Samples.Dynamic
{
    public static class ShuffleRows
    {
        // Sample class showing how to shuffle rows in 
        // IDataView.
        public static void Example()
        {
            // Create a new context for ML.NET operations. It can be used for
            // exception tracking and logging, as a catalog of available operations
            // and as the source of randomness.
            var mlContext = new MLContext();

            // Get a small dataset as an IEnumerable.
            var enumerableOfData = GetSampleTemperatureData(5);
            var data = mlContext.Data.LoadFromEnumerable(enumerableOfData);

            // Before we apply a filter, examine all the records in the dataset.
            Console.WriteLine($"Date\tTemperature");
            foreach (var row in enumerableOfData)
            {
                Console.WriteLine($"{row.Date.ToString("d")}" +
                    $"\t{row.Temperature}");
            }
            Console.WriteLine();
            // Expected output:
            //  Date    Temperature
            //  1/2/2012        36
            //  1/3/2012        36
            //  1/4/2012        34
            //  1/5/2012        35
            //  1/6/2012        35

            // Shuffle the dataset.
            var shuffledData = mlContext.Data.ShuffleRows(data, seed: 123);

            // Look at the shuffled data and observe that the rows are in a
            // randomized order.
            var enumerable = mlContext.Data
                .CreateEnumerable<SampleTemperatureData>(shuffledData,
                reuseRowObject: true);

            Console.WriteLine($"Date\tTemperature");
            foreach (var row in enumerable)
            {
                Console.WriteLine($"{row.Date.ToString("d")}" +
                $"\t{row.Temperature}");
            }
            // Expected output:
            //  Date    Temperature
            //  1/4/2012        34
            //  1/2/2012        36
            //  1/5/2012        35
            //  1/3/2012        36
            //  1/6/2012        35
        }

        private class SampleTemperatureData
        {
            public DateTime Date { get; set; }
            public float Temperature { get; set; }
        }

        /// <summary>
        /// Get a fake temperature dataset.
        /// </summary>
        /// <param name="exampleCount">The number of examples to return.</param>
        /// <returns>An enumerable of <see cref="SampleTemperatureData"/>.</returns>
        private static IEnumerable<SampleTemperatureData> GetSampleTemperatureData(
            int exampleCount)

        {
            var rng = new Random(1234321);
            var date = new DateTime(2012, 1, 1);
            float temperature = 39.0f;

            for (int i = 0; i < exampleCount; i++)
            {
                date = date.AddDays(1);
                temperature += rng.Next(-5, 5);
                yield return new SampleTemperatureData
                {
                    Date = date,
                    Temperature =
                    temperature
                };

            }
        }
    }
}

注解

ShuffleRows(IDataView, Nullable<Int32>, Int32, Boolean) 将使用流式处理方法随机排列任何输入 IDataView 的行。 为了不在内存中加载整个数据集，将使用行池随机选择要输出的 shufflePoolSize 行。 池是从第一 shufflePoolSize 行构造的 input。 然后，将从池中随机生成行，并将下一行替换为下一行 input ，直到生成所有行，从而产生与随机顺序的行相同的新 IDataView 大小 input 。 CanShuffle如果属性input为 true，则也会按随机顺序将其读入池，提供两个随机源。