bayesredis 1.0.1

A Simple Naive Bayes Classifier in Python

Naive Bayes Classifier is an algorithm to classify texts into sets that is always learning.

The most obvious practical use of it is for Email Spam/Ham Detection.

Motivation

There is a really good video piece in Youtube [here](http://www.youtube.com/watch?v=yvDCzhbjYWs) by [Peter Norvig](http://en.wikipedia.org/wiki/Peter_Norvig), Director of Research at Google. He spoke about The Unreasonable Effectiveness of Data.

Another great piece about the algorithm explained in plain English is by [Alexander Nedelcu](https://www.bionicspirit.com/pages/about.html) with his [blog post here](http://bionicspirit.com/blog/2012/02/09/howto-build-naive-bayes-classifier.html).

Implementation

Before meddling with Python, I translated Alexander’s implementation in Ruby to PHP available [here](https://github.com/tistaharahap/Simple-Naive-Bayes-Classifier-for-PHP).

Benchmarking my oven fresh PHP implementation at the time, [Redis](http://redis.io) was the only answer to achieve sub-second results. I tried MySQL and MongoDB before Redis.

External Dependencies

• Redis <http://redis.io>

• [Optional - For Data Import only] MySQL Python Connector <http://dev.mysql.com/doc/connector-python/en/index.html>

Use Examples

Please take a look at [test.py](https://github.com/tistaharahap/python-bayes-redis/blob/master/test.py) for executing the classifier.

To import data using MySQL, take a look at [test-import-mysql.py](https://github.com/tistaharahap/python-bayes-redis/blob/master/test-import-mysql.py).

Performance

The gear and spec used to test performance is below: - Macbook Pro Early 2011 - Intel Core i5 2.3 GHz - 8 GB PC-10600 DDR3 RAM - SSD - Redis v2.6.13 compiled from source - Python v2.7.2

The data sets is as below: - 1,212 Sets - 311,525 Keywords

Classifying Time: - 1 Keyword - PHP @ 0.01428 second – 0.0569310188293 second <Python v2.7.2 Mac> – 0.178730964661 second <PyPy v2.0.2 Mac> - 2 Keywords - PHP @ 0.02171 second – 0.0672879219055 second <Python v2.7.2 Mac> – 0.226923942566 second <PyPy v2.0.2 Mac> - 3 Keywords - PHP @ 0.04062 second – 0.088278055191 second <Python v2.7.2 Mac> – 0.246510982513 second <PyPy v2.0.2 Mac>

Optimization

Anything worthy being converted to a list/dict comprehension for