Metadata-Version: 1.1
Name: mfnbc
Version: 1.1
Summary: UNKNOWN
Home-page: https://github.com/shawnzam/mfnbc
Author: Shawn
Author-email: shawnzam@gmail.com
License: The MIT License (MIT)
Description: # MFNBC
        
        ###Requiremnts
        Python >= 3.3
        
        ###Install
        
        ```
        pip install mfnbc
        ```
        
        ###Setup (Likeihood Input File)
        It is assumed you have a word based likelihood table (csv file) where the headers consists of the literal word `Word` and the remaining columns are the features you would like to classify.
        
        For example:
        
        <table style="border-collapse: collapse; width: 260pt;" border="1" width="348" cellspacing="0" cellpadding="0">
        <colgroup>
        <col style="width: 65pt;" span="4" width="87" /> </colgroup>
        <tbody>
        <tr style="height: 16.0pt;">
        <td style="height: 16.0pt; width: 65pt;" width="87" height="21"><strong>Word</strong></td>
        <td style="width: 65pt;" width="87">Animal</td>
        <td style="width: 65pt;" width="87">Human</td>
        <td style="width: 65pt;" width="87">Plant</td>
        </tr>
        <tr style="height: 16.0pt;">
        <td style="height: 16.0pt;" height="21">cat</td>
        <td align="right">0.33</td>
        <td align="right">0.03</td>
        <td align="right">0.05</td>
        </tr>
        <tr style="height: 16.0pt;">
        <td style="height: 16.0pt;" height="21">dog</td>
        <td align="right">0.33</td>
        <td align="right">0.02</td>
        <td align="right">0.05</td>
        </tr>
        <tr style="height: 16.0pt;">
        <td style="height: 16.0pt;" height="21">leaves</td>
        <td align="right">0.05</td>
        <td align="right">0.03</td>
        <td align="right">0.4</td>
        </tr>
        <tr style="height: 16.0pt;">
        <td style="height: 16.0pt;" height="21">tree</td>
        <td align="right">0.05</td>
        <td align="right">0.02</td>
        <td align="right">0.4</td>
        </tr>
        <tr style="height: 16.0pt;">
        <td style="height: 16.0pt;" height="21">man</td>
        <td align="right">0.12</td>
        <td align="right">0.45</td>
        <td align="right">0.05</td>
        </tr>
        <tr style="height: 16.0pt;">
        <td style="height: 16.0pt;" height="21">women</td>
        <td align="right">0.12</td>
        <td align="right">0.45</td>
        <td align="right">0.05</td>
        </tr>
        </tbody>
        </table>
        
        ###Setup (Unlabeled Data File)
        The key is having the header titled  `Text` any other fields will be included unmodified in the output file.
        
        
        <table style="border-collapse: collapse; width: 460pt;" border="1" width="348" cellspacing="0" cellpadding="0">
        <colgroup>
        <col style="width: 65pt;" span="4" width="87" /> </colgroup>
        <tbody>
        <tr>
        <td width="87">ID</td>
        <td width="356"><strong>Text</strong></td>
        </tr>
        <tr>
        <td>1</td>
        <td>The cat is my pet and he is lovley. A dog will not do.</td>
        </tr>
        <tr>
        <td>2</td>
        <td>The man and women had a cat and lived under a tree</td>
        </tr>
        <tr>
        <td>3</td>
        <td>The tree had lots of leaves</td>
        </tr>
        <tr>
        <td>4</td>
        <td>A man lives under a tree with many leaves. A women has a cat as a pet</td>
        </tr>
        <tr>
        <td>5</td>
        <td>The dog and cat chanse the man under the tree</td>
        </tr>
        <tr>
        <td>6</td>
        <td>The man and women live in a house.</td>
        </tr>
        </tbody>
        </table>
        
        ###Import
        
        ```python
        from mfnbc import MFNBC
        ```
        ### Instantiate
        
        ```python
        m = MFNBC(<likelihoods_input_file - location of Likelihood table (str)>,
                  <unlabeled_data_file - Location of unlabeled data file (str)>,
                  <verbose output - Turn on of off verbose output, default: off>
        ```
        ###Example
        ```python
        m = MFNBC('likeli_sample.csv', 'input_sample.csv', False)
        m.write_csv()
        ```
        You can also print the probability table by
        
        ```python
        m.probs
        ```
        
        ###Example Results
        
        <table style="border-collapse: collapse; width: 460pt;" border="1" width="348" cellspacing="0" cellpadding="0">
        <colgroup>
        <col style="width: 65pt;" span="4" width="87" /> </colgroup>
        <tbody>
        <tr style="height: 16.0pt;">
        <td style="height: 16.0pt; width: 65pt;" width="87" height="21">ID</td>
        <td style="width: 65pt;" width="87">reviewText</td>
        <td style="width: 65pt;" width="87">Animal</td>
        <td style="width: 65pt;" width="87">Human</td>
        <td style="width: 65pt;" width="87">Plant</td>
        </tr>
        <tr style="height: 16.0pt;">
        <td style="height: 16.0pt;" align="right" height="21">1</td>
        <td>The cat is my pet and he is lovley. A dog will not do.</td>
        <td align="right">0.972321429</td>
        <td align="right">0.005357143</td>
        <td align="right">0.022321429</td>
        </tr>
        <tr style="height: 16.0pt;">
        <td style="height: 16.0pt;" align="right" height="21">2</td>
        <td>The man and women had a cat and lived under a tree</td>
        <td align="right">0.580787094</td>
        <td align="right">0.2969934</td>
        <td align="right">0.122219506</td>
        </tr>
        <tr style="height: 16.0pt;">
        <td style="height: 16.0pt;" align="right" height="21">3</td>
        <td>The tree had lots of leaves</td>
        <td align="right">0.01532802</td>
        <td align="right">0.003678725</td>
        <td align="right">0.980993256</td>
        </tr>
        <tr style="height: 16.0pt;">
        <td style="height: 16.0pt;" align="right" height="21">4</td>
        <td>A man lives under a tree with many leaves. A women has a cat as a pet</td>
        <td align="right">0.334412386</td>
        <td align="right">0.1026038</td>
        <td align="right">0.562983814</td>
        </tr>
        <tr style="height: 16.0pt;">
        <td style="height: 16.0pt;" align="right" height="21">5</td>
        <td>The dog and cat chanse the man under the tree</td>
        <td align="right">0.921839729</td>
        <td align="right">0.00761851</td>
        <td align="right">0.070541761</td>
        </tr>
        <tr style="height: 16.0pt;">
        <td style="height: 16.0pt;" align="right" height="21">6</td>
        <td>The man and women live in a house.</td>
        <td align="right">0.065633546</td>
        <td align="right">0.922971741</td>
        <td align="right">0.011394713</td>
        </tr>
        </tbody>
        </table>
        
        
Keywords: bayes
Platform: UNKNOWN
Classifier: Programming Language :: Python :: 3
Classifier: Natural Language :: English
Classifier: Topic :: Scientific/Engineering :: Information Analysis
