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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; }
}
}
}
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