Metadata-Version: 2.1
Name: niacin
Version: 0.1.0
Summary: UNKNOWN
Home-page: UNKNOWN
License: UNKNOWN
Description: # niacin
        
        A Python library for replacing the missing variation in your data.
        
        ## Why should I use this?
        
        Data collected for model training necessarily undersamples the likely
        variance in the input space. This library is a collection of tools for
        inserting typical kinds of perturbations to better approximate population
        variance; and, for creating similar-but-incorrect examples to aid in
        reducing the total size of the hypothesis space. These are commonly known as
        <small>ENRICHMENT</small> and <small>NEGATIVE SAMPLING</small>, respectively.
        
        ## How do I use this?
        
        Functions in niacin are separated into submodules for specific data types.
        Functions expose a similar API, with two input arguments: the data to be
        transformed, and the probability of applying a specific transformation.
        
        enrichment:
        
        ```python
        data = "This is the song that never ends and it goes on and on my friends"
        print(text.add_misspelling(data, p=1.0))
        ```
        
        ```output
        This is teh song tath never ends adn it goes on anbd on my firends
        ```
        
        negative sampling:
        
        ```python
        data = "This is the song that never ends and it goes on and on my friends"
        print(text.add_hypernyms(data, p=1.0))
        ```
        
        ```output
        This is the musical composition that never extremity and it exit on and on my person
        ```
        
        ## How do I install this?
        
        with `pip`:
        
        ```sh
        pip install niacin
        ```
        
        from source:
        
        ```sh
        git clone git@github.com:deniederhut/niacin.git && cd niacin && python setup.py install
        ```
        
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Description-Content-Type: text/markdown
