simplebayes package

Module contents

The MIT License (MIT)

Copyright (c) 2015 Ryan Vennell

Permission is hereby granted, free of charge, to any person obtaining a copy of this software and associated documentation files (the “Software”), to deal in the Software without restriction, including without limitation the rights to use, copy, modify, merge, publish, distribute, sublicense, and/or sell copies of the Software, and to permit persons to whom the Software is furnished to do so, subject to the following conditions:

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class simplebayes.SimpleBayes(tokenizer=None, cache_path='/tmp/')[source]

Bases: object

A memory-based, optional-persistence naïve bayesian text classifier.

cache_file = '_simplebayes.pickle'
cache_persist()[source]

Saves the current trained data to the cache. This is initiated by the program using this module

cache_train()[source]

Loads the data for this classifier from a cache file

Returns:whether or not we were successful
Return type:bool
calculate_bayesian_probability(cat, token_score, token_tally)[source]

Calculates the bayesian probability for a given token/category

Parameters:
  • cat (str) – The category we’re scoring for this token
  • token_score (float) – The tally of this token for this category
  • token_tally (float) – The tally total for this token from all categories
Returns:

bayesian probability

Return type:

float

calculate_category_probability()[source]

Caches the individual probabilities for each category

classify(text)[source]

Chooses the highest scoring category for a sample of text

Parameters:text (str) – sample text to classify
Returns:the “winning” category
Return type:str
classmethod count_token_occurrences(words)[source]

Creates a key/value set of word/count for a given sample of text

Parameters:words (list) – full list of all tokens, non-unique
Returns:key/value pairs of words and their counts in the list
Return type:dict
flush()[source]

Deletes all tokens & categories

get_cache_location()[source]

Gets the location of the cache file

Returns:the location of the cache file
Return type:string
score(text)[source]

Scores a sample of text

Parameters:text (str) – sample text to score
Returns:dict of scores per category
Return type:dict
tally(category)[source]

Gets the tally for a requested category

Parameters:category (str) – The category we want a tally for
Returns:tally for a given category
Return type:int
classmethod tokenize_text(text)[source]

Default tokenize method; can be overridden

Parameters:text (str) – the text we want to tokenize
Returns:list of tokenized text
Return type:list
train(category, text)[source]

Trains a category with a sample of text

Parameters:
  • category (str) – the name of the category we want to train
  • text (str) – the text we want to train the category with
untrain(category, text)[source]

Untrains a category with a sample of text

Parameters:
  • category (str) – the name of the category we want to train
  • text (str) – the text we want to untrain the category with