TextCatalog.RemoveDefaultStopWords Método

Definición

Espacio de nombres:

Microsoft.ML

Ensamblado:

Microsoft.ML.Transforms.dll

Paquete:

Microsoft.ML v2.0.0

Cree un CustomStopWordsRemovingEstimatorobjeto , que copia los datos de la columna especificada en inputColumnName en una nueva columna: outputColumnName y quita el conjunto predifined de texto específico para language él.

public static Microsoft.ML.Transforms.Text.StopWordsRemovingEstimator RemoveDefaultStopWords (this Microsoft.ML.TransformsCatalog.TextTransforms catalog, string outputColumnName, string inputColumnName = default, Microsoft.ML.Transforms.Text.StopWordsRemovingEstimator.Language language = Microsoft.ML.Transforms.Text.StopWordsRemovingEstimator+Language.English);

static member RemoveDefaultStopWords : Microsoft.ML.TransformsCatalog.TextTransforms * string * string * Microsoft.ML.Transforms.Text.StopWordsRemovingEstimator.Language -> Microsoft.ML.Transforms.Text.StopWordsRemovingEstimator

<Extension()>
Public Function RemoveDefaultStopWords (catalog As TransformsCatalog.TextTransforms, outputColumnName As String, Optional inputColumnName As String = Nothing, Optional language As StopWordsRemovingEstimator.Language = Microsoft.ML.Transforms.Text.StopWordsRemovingEstimator+Language.English) As StopWordsRemovingEstimator

Parámetros

catalog

TransformsCatalog.TextTransforms

Catálogo de la transformación.

outputColumnName

String

Nombre de la columna resultante de la transformación de inputColumnName. El tipo de datos de esta columna será un vector de tamaño variable del texto.

inputColumnName

String

Nombre de la columna desde la que se van a copiar los datos. Este estimador funciona sobre el vector de texto.

language

StopWordsRemovingEstimator.Language

Langauge de la columna inputColumnNamede texto de entrada .

Devoluciones

StopWordsRemovingEstimator

Ejemplos

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

namespace Samples.Dynamic
{
    public static class RemoveDefaultStopWords
    {
        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 an empty list as the dataset. The 'RemoveDefaultStopWords'
            // does not require training data as the estimator 
            // ('StopWordsRemovingEstimator') created by 'RemoveDefaultStopWords'
            // API is not a trainable estimator. The empty list is only needed to
            // pass input schema to the pipeline.
            var emptySamples = new List<TextData>();

            // Convert sample list to an empty IDataView.
            var emptyDataView = mlContext.Data.LoadFromEnumerable(emptySamples);

            // A pipeline for removing stop words from input text/string.
            // The pipeline first tokenizes text into words then removes stop words.
            // The 'RemoveDefaultStopWords' API ignores casing of the text/string
            // e.g. 'tHe' and 'the' are considered the same stop words.
            var textPipeline = mlContext.Transforms.Text.TokenizeIntoWords("Words",
                "Text")
                .Append(mlContext.Transforms.Text.RemoveDefaultStopWords(
                "WordsWithoutStopWords", "Words", language:
                StopWordsRemovingEstimator.Language.English));

            // Fit to data.
            var textTransformer = textPipeline.Fit(emptyDataView);

            // Create the prediction engine to remove the stop words from the input
            // text /string.
            var predictionEngine = mlContext.Model.CreatePredictionEngine<TextData,
                TransformedTextData>(textTransformer);

            // Call the prediction API to remove stop words.
            var data = new TextData()
            {
                Text = "ML.NET's RemoveDefaultStopWords " +
                "API removes stop words from tHe text/string. It requires the " +
                "text/string to be tokenized beforehand."
            };

            var prediction = predictionEngine.Predict(data);

            // Print the length of the word vector after the stop words removed.
            Console.WriteLine("Number of words: " + prediction.WordsWithoutStopWords
                .Length);

            // Print the word vector without stop words.
            Console.WriteLine("\nWords without stop words: " + string.Join(",",
                prediction.WordsWithoutStopWords));

            //  Expected output:
            //   Number of words: 11
            //   Words without stop words: ML.NET's,RemoveDefaultStopWords,API,removes,stop,words,text/string.,requires,text/string,tokenized,beforehand.
        }

        private class TextData
        {
            public string Text { get; set; }
        }

        private class TransformedTextData : TextData
        {
            public string[] WordsWithoutStopWords { get; set; }
        }
    }
}