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ML.NET.Classification.Metrics.Library is an extension library for ML.NET that adds detailed ROC curve generation and AUC calculation.

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Bgajski/ML.NET.Classification.Metrics.Library

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ML.NET.Classification.Metrics.Library

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ML.NET.Classification.Metrics.Library is an extension library for ML.NET that adds detailed ROC curve generation and AUC calculation complementing ML.NET’s built-in metrics with richer visualization and custom threshold analysis

Key Features

  • ROC curve generation: Produces FPR/TPR arrays by sweeping (threshold bins + 1) from 1.0 to 0.0, giving a smooth approximation
  • Custom threshold bins: Choose the number of bins to balance speed and fidelity
  • Consistent AUC: Computes AUC via trapezoidal integration over the same ROC points, ensuring the curve and scalar metric stay aligned
  • Interop-ready: Returns strongly-typed .NET structs, making results easy to visualize in charts, diagnostics, or reporting tools

NuGet package

  1. Add the NuGet package:
  • dotnet add package ML.NET.Classification.Metrics --version 0.1.0
  1. Import the namespace in your code
  • using ML.NET.Metrics.Evaluation;

Libraries

  • .NET 8.0
  • Windows x64 native binary

About

ML.NET.Classification.Metrics.Library is an extension library for ML.NET that adds detailed ROC curve generation and AUC calculation.

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