DataOperationsCatalog.FilterRowsByMissingValues(IDataView, String[]) 方法
定義
重要
部分資訊涉及發行前產品,在發行之前可能會有大幅修改。 Microsoft 對此處提供的資訊,不做任何明確或隱含的瑕疵擔保。
卸載中 columns
任何資料行包含遺漏值的資料列。
public Microsoft.ML.IDataView FilterRowsByMissingValues (Microsoft.ML.IDataView input, params string[] columns);
member this.FilterRowsByMissingValues : Microsoft.ML.IDataView * string[] -> Microsoft.ML.IDataView
Public Function FilterRowsByMissingValues (input As IDataView, ParamArray columns As String()) As IDataView
參數
- input
- IDataView
輸入資料。
- columns
- String[]
要篩選的資料行名稱。 如果資料列在任何資料行中都有遺漏的值,則會從資料集卸載。
傳回
範例
using System;
using System.Collections.Generic;
using Microsoft.ML;
using Microsoft.ML.SamplesUtils;
namespace Samples.Dynamic
{
public class FilterRowsByMissingValues
{
/// <summary>
/// Sample class showing how to use FilterRowsByMissingValues.
/// </summary>
public static void Example()
{
// Create a new ML context, for ML.NET operations. It can be used for
// exception tracking and logging, as well as the source of randomness.
var mlContext = new MLContext();
// Create a small dataset as an IEnumerable.
var samples = new List<DataPoint>()
{
new DataPoint(){ Feature1 = 21, Feature2 = new [] { 1, 2, float.NaN}
},
new DataPoint(){ Feature1 = 40, Feature2 = new [] { 1f, 2f, 3f} },
new DataPoint(){ Feature1 = float.NaN, Feature2 = new [] { 1, 2,
float.NaN} }
};
// Convert training data to IDataView.
var data = mlContext.Data.LoadFromEnumerable(samples);
// Filter out any row with an NaN values in either column
var filteredData = mlContext.Data
.FilterRowsByMissingValues(data, new[] { "Feature1", "Feature2" });
// Take a look at the resulting dataset and note that rows with NaNs are
// filtered out. Only the second data point is left
var enumerable = mlContext.Data
.CreateEnumerable<DataPoint>(filteredData, reuseRowObject: true);
Console.WriteLine($"Feature1 Feature2");
foreach (var row in enumerable)
{
Console.WriteLine($"{row.Feature1}" +
$"\t({string.Join(", ", row.Feature2)})");
}
// Feature1 Feature2
//
// 40 (1, 2, 3)
}
private class DataPoint
{
public float Feature1 { get; set; }
public float[] Feature2 { get; set; }
}
}
}
適用於
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