Python下开源可持久化朴素贝叶斯分类库：simplebayes

simplebayes是Python下开源可持久化朴素贝叶斯分类库。

This work is heavily inspired by the python "redisbayes" module found here:  [https://github.com/jart/redisbayes] and [https://pypi.python.org/pypi/redisbayes]    I've elected to write this to alleviate the network/time requirements when  using the bayesian classifier to classify large sets of text, or when  attempting to train with very large sets of sample data.

Installation

sudo pip install simplebayes

Basic Usage

import simplebayes  bayes = simplebayes.SimpleBayes()    bayes.train('good', 'sunshine drugs love sex lobster sloth')  bayes.train('bad', 'fear death horror government zombie')    assert bayes.classify('sloths are so cute i love them') == 'good'  assert bayes.classify('i would fear a zombie and love the government') == 'bad'    print bayes.score('i fear zombies and love the government')

Cache Usage

import simplebayes  bayes = simplebayes.SimpleBayes(cache_path='/my/cache/')  # Cache file is '/my/cache/_simplebayes.pickle'  # Default cache_path is '/tmp/'    if not bayes.cache_train():      # Unable to load cache data, so we're training it      bayes.train('good', 'sunshine drugs love sex lobster sloth')      bayes.train('bad', 'fear death horror government zombie')        # Saving the cache so next time the training won't be needed      bayes.persist_cache()

Tokenizer Override

import simplebayes    def my_tokenizer(sample):      return sample.split()    bayes = simplebayes.SimpleBayes(tokenizer=my_tokenizer)

项目主页：http://www.open-open.com/lib/view/home/1427787192959