a text classification library https://github.com/aneksteind/hext#readme

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BSD3 licensed by David Anekstein
Maintained by aneksteind@gmail.com


This is currently the beginning of a text classification library.


`stack install hext`

hackage - https://hackage.haskell.org/package/hext-

To run:

`stack build`

`stack exec hext-exe`


Currently, the only algorithm implementation is the Naive Bayes algorithm: to run your own data through this algorithm in order to classify your text, you need: - classified data: this can be sourced from a database where the only fields that are needed are the text itself, and it's class - a sample string which will be classified by the algorithm

In order to run the program, the classified data specified above must be converted into a `BayesModel a using the teach function, where a is your own defined data type representing the class to classify your text. Your class must be and instance of Ord and Eq`.

With your new `BayesModel filled with knowledge, it's time to classify your text using runBayes. An example of this can be seen in app/Main.hs where data Class = Positive | Negative deriving (Eq, Ord, Show)` to label movie reviews as either positive or negative.


I encourage contributing to this package, in the form of implementing algorithms that are not yet in the project, improving efficiency, or the like.

Used by 1 package:
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