TextCatalog.NormalizeText 메서드

정의

네임스페이스:

Microsoft.ML

어셈블리:

Microsoft.ML.Transforms.dll

패키지:

Microsoft.ML v2.0.0

Creates a TextNormalizingEstimator, which normalizes incoming text in inputColumnName by optionally changing case, removing diacritical marks, punctuation marks, numbers, and outputs new text as outputColumnName.

public static Microsoft.ML.Transforms.Text.TextNormalizingEstimator NormalizeText (this Microsoft.ML.TransformsCatalog.TextTransforms catalog, string outputColumnName, string inputColumnName = default, Microsoft.ML.Transforms.Text.TextNormalizingEstimator.CaseMode caseMode = Microsoft.ML.Transforms.Text.TextNormalizingEstimator+CaseMode.Lower, bool keepDiacritics = false, bool keepPunctuations = true, bool keepNumbers = true);

static member NormalizeText : Microsoft.ML.TransformsCatalog.TextTransforms * string * string * Microsoft.ML.Transforms.Text.TextNormalizingEstimator.CaseMode * bool * bool * bool -> Microsoft.ML.Transforms.Text.TextNormalizingEstimator

<Extension()>
Public Function NormalizeText (catalog As TransformsCatalog.TextTransforms, outputColumnName As String, Optional inputColumnName As String = Nothing, Optional caseMode As TextNormalizingEstimator.CaseMode = Microsoft.ML.Transforms.Text.TextNormalizingEstimator+CaseMode.Lower, Optional keepDiacritics As Boolean = false, Optional keepPunctuations As Boolean = true, Optional keepNumbers As Boolean = true) As TextNormalizingEstimator

매개 변수

catalog

TransformsCatalog.TextTransforms

텍스트 관련 변환의 카탈로그입니다.

outputColumnName

String

의 변환에서 생성된 열의 inputColumnName이름입니다. 이 열의 데이터 형식은 입력 열 데이터 형식에 따라 스칼라 또는 텍스트 벡터입니다.

inputColumnName

String

변환할 열의 이름입니다. 이 값으로 null설정하면 해당 값이 outputColumnName 원본으로 사용됩니다. 이 추정기는 텍스트 데이터 형식의 텍스트 또는 벡터에서 작동합니다.

caseMode

TextNormalizingEstimator.CaseMode

고정 문화권의 규칙을 사용하여 텍스트 대/소문자를 지정합니다.

keepDiacritics

Boolean

음의 표시를 유지할지 또는 제거할지 여부입니다.

keepPunctuations

Boolean

문장 부호를 유지할지 또는 제거할지 여부입니다.

keepNumbers

Boolean

숫자를 유지할지 아니면 제거할지 여부입니다.

반환

TextNormalizingEstimator

예제

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

namespace Samples.Dynamic
{
    public static class NormalizeText
    {
        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 'NormalizeText' API does not
            // require training data as the estimator ('TextNormalizingEstimator')
            // created by 'NormalizeText' 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 normalizing text.
            var normTextPipeline = mlContext.Transforms.Text.NormalizeText(
                "NormalizedText", "Text", TextNormalizingEstimator.CaseMode.Lower,
                keepDiacritics: false,
                keepPunctuations: false,
                keepNumbers: false);

            // Fit to data.
            var normTextTransformer = normTextPipeline.Fit(emptyDataView);

            // Create the prediction engine to get the normalized text from the
            // input text/string.
            var predictionEngine = mlContext.Model.CreatePredictionEngine<TextData,
                TransformedTextData>(normTextTransformer);

            // Call the prediction API.
            var data = new TextData()
            {
                Text = "ML.NET's NormalizeText API " +
                "changes the case of the TEXT and removes/keeps diâcrîtîcs, " +
                "punctuations, and/or numbers (123)."
            };

            var prediction = predictionEngine.Predict(data);

            // Print the normalized text.
            Console.WriteLine($"Normalized Text: {prediction.NormalizedText}");

            //  Expected output:
            //   Normalized Text: mlnets normalizetext api changes the case of the text and removeskeeps diacritics punctuations andor numbers
        }

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

        private class TransformedTextData : TextData
        {
            public string NormalizedText { get; set; }
        }
    }
}