// Copyright © Benjamin Abt 2021, all rights reserved

using Microsoft.ML;

using Microsoft.ML.Calibrators;

using Microsoft.ML.Data;

using Microsoft.ML.Trainers.FastTree;

using Spectre.Console;

namespace ToxicSentimentSample

{

public static class BinaryClassification

{

public static EstimatorChain<BinaryPredictionTransformer<CalibratedModelParametersBase<FastTreeBinaryModelParameters, PlattCalibrator>>>

CreatePipeline(MLContext mlContext)

{

EstimatorChain<BinaryPredictionTransformer<CalibratedModelParametersBase<FastTreeBinaryModelParameters, PlattCalibrator>>> pipeline

= mlContext.Transforms.Text.FeaturizeText(

outputColumnName: "Features",

inputColumnName: nameof(TrainInput.Text))

// step 2: add a fast tree learner

.Append(mlContext.BinaryClassification.Trainers.FastTree(

labelColumnName: nameof(TrainInput.IsToxic),

featureColumnName: "Features"));

return pipeline;

}

public static CalibratedBinaryClassificationMetrics Validate(MLContext mlContext, IDataView predictions)

=> mlContext.BinaryClassification.Evaluate(predictions, labelColumnName: nameof(TrainInput.IsToxic));

public static void PrintMetrics(CalibratedBinaryClassificationMetrics metrics)

{

AnsiConsole.MarkupLine($"=> metrics for binary classification");

Table trt = new();

{

trt.AddColumn(new TableColumn("Name").RightAligned());

trt.AddColumn("Value");

}

trt.AddRow("Accuracy", $"{metrics.Accuracy:P2}");

trt.AddRow("Area Under Precision Recall Curve", $"{metrics.AreaUnderPrecisionRecallCurve:P2}");

trt.AddRow("Area Under Roc Curve", $"{metrics.AreaUnderRocCurve:P2}");

trt.AddRow("F1 Score", $"{metrics.F1Score:P2}");

trt.AddRow("Log Loss", $"{metrics.LogLoss:0.##}");

trt.AddRow("Log Loss Reduction", $"{metrics.LogLossReduction:0.##}");

trt.AddRow("Positive Precision", $"{metrics.PositivePrecision:0.##}");

trt.AddRow("Positive Recall", $"{metrics.PositiveRecall:0.##}");

trt.AddRow("Negative Precision", $"{metrics.NegativePrecision:0.##}");

trt.AddRow("Negative Recall", $"{metrics.NegativeRecall:0.##}");

AnsiConsole.Render(trt);

}

}

}