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A lightweight and easy-to-use Dart library for evaluating machine learning models. Includes accuracy, precision, recall, F1 score, and confusion matrix for binary classification.

Changelog #


0.1.0 - 2025-07-13 #

Added #

  • Initial release of ml_metrics.
  • Implemented accuracy, precision, recall, f1Score metrics.
  • Added binaryConfusionMatrix function.
  • Exported metrics via central ml_metrics.dart file.
  • Included unit tests for all metric functions.
  • Prepared documentation: README.md, LICENSE, and this CHANGELOG.md.

[Unreleased] #

Planned #

  • ROC AUC metric
  • Multi-class support for metrics
  • Visual confusion matrix builder
  • Integration with ml_knn, ml_logistic_regression, etc.
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A lightweight and easy-to-use Dart library for evaluating machine learning models. Includes accuracy, precision, recall, F1 score, and confusion matrix for binary classification.

Repository (GitHub)
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Topics

#machine-learning #metrics #evaluation #classification #dart

Documentation

API reference

License

MIT (license)

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