simplebayes是Python下開源可持久化樸素貝葉斯分類庫。

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.</pre> 
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')</pre>

</div>
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()</pre></h2>

Tokenizer Override 
import simplebayes

def my_tokenizer(sample):
    return sample.split()
bayes = simplebayes.SimpleBayes(tokenizer=my_tokenizer)</pre></h2>
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 算法 simplebayes