fredwu/simple_bayes

A Naive Bayes machine learning implementation in Elixir.

31
/ 100
Emerging

Supports three distinct classifier models (multinomial, binarized multinomial, and Bernoulli) with pluggable storage backends—memory, file system, or Erlang's Dets—enabling flexible deployment from in-memory classification to persistent, disk-based learning. Includes preprocessing capabilities like stop-word filtering, additive smoothing, TF-IDF weighting, optional word stemming, and per-training-example keyword weighting for fine-grained model tuning.

396 stars. No commits in the last 6 months.

No License Stale 6m No Package No Dependents
Maintenance 0 / 25
Adoption 10 / 25
Maturity 8 / 25
Community 13 / 25

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Stars

396

Forks

24

Language

Elixir

License

Last pushed

Sep 25, 2017

Commits (30d)

0

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