Simple Bayes

Simple Bayes

This Naive Bayes implementation in Elixir offers a robust tool for probabilistic classification, ideal for tasks such as text categorization and medical diagnosis. Leveraging Bayes' theorem with strong independence assumptions, it ensures efficient training and scalability, making it a competitive choice against more complex classifiers while providing flexible storage options.

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Top Simple Bayes Features

  • Elixir-based implementation
  • Strong independence assumptions
  • Text categorization support
  • Efficient maximum-likelihood training
  • Scalable parameter requirements
  • Simple installation process
  • Optional word stemming functionality
  • In-memory storage option
  • File system encoding speed
  • Dets library integration
  • Compatibility with older Elixir versions
  • User-configurable options
  • Base64 data encoding
  • Performance optimization comparisons
  • Feedback-driven improvements
  • Open-source MIT license
  • Document category classification
  • Automatic medical diagnosis application
  • Competitive with advanced methods.