TextCatalog.RemoveDefaultStopWords Method

Definition

Namespace:

Microsoft.ML

Assembly:

Microsoft.ML.Transforms.dll

Package:

Microsoft.ML v3.0.1

Create a CustomStopWordsRemovingEstimator, which copies the data from the column specified in inputColumnName to a new column: outputColumnName and removes predifined set of text specific for language from it.

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

Parameters

catalog

TransformsCatalog.TextTransforms

The transform's catalog.

outputColumnName

String

Name of the column resulting from the transformation of inputColumnName. This column's data type will be variable-size vector of text.

inputColumnName

String

Name of the column to copy the data from. This estimator operates over vector of text.

language

StopWordsRemovingEstimator.Language

Langauge of the input text column inputColumnName.

Returns

StopWordsRemovingEstimator

Examples

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; }
        }
    }
}