Bayesian classifier on top of Redis
Python Ruby
Switch branches/tags
Nothing to show
Clone or download
Fetching latest commit…
Cannot retrieve the latest commit at this time.
Failed to load latest commit information.


What is BayesOnRedis?

Bayesian classifier on top of Redis

Why on Redis?

Redis is a persistent, in-memory, key-value store with support for various data structures such as lists, sets, and ordered sets. All these data types can be manipulated with atomic operations to push/pop elements, add/remove elements, perform server-side union, intersection, difference between sets, and so forth.

Because of Redis' properties:

  • It is extremely easy to implement simple algorithm such as bayesian filter.

  • The persistence of Redis means that the Bayesian implementation can be used in real production environment.

  • Even though I don't particularly care about performance at the moment, Redis benchmarks give me confidence that the implementation can scale to relatively large training data.

How to install? (Ruby version)

gem install bayes_on_redis

Getting started

# Require BayesOnRedis and RubyGems
require "rubygems"
require "bayes_on_redis"

# Create instance of BayesOnRedis and pass your Redis information.
# Of course, use real sentences for much better accuracy.
# Unless if you want to train spam related things.
bor = => '', :redis_port => 6379, :redis_db => 0)

# Teach it
bor.train "good", "sweet awesome kick-ass cool pretty smart"
bor.train "bad", "sucks lame boo death bankrupt loser sad"

# Then ask it to classify text.
bor.classify("awesome kick-ass ninja can still be lame.")

for Pythonistas

BayesOnRedis is also available in Python. With the same API.

easy_install bayes_on_redis


Fork and send pull requests.