# hext
This is currently the beginning of a text classification library.

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 run through the ```makeMaterial``` function in ```NLP.Hext.NaiveBayes```.

Before doing this, however, you must create a data type, its data constructors each representing a class to label each text sample with. An example of this can be seen in ```app/Main.hs``` where ```data Class = Positive | Negative deriving (Eq, Show)``` to label movie reviews as positive or negative.

Now that the learning material has been made with ```makeMaterial```, it, along with a new string for the algorithm to classify, can be passed into runBayes like so: ```runBayes material "This is a sample review"```. An example, along with sample data, can be seen in ```app/Main.hs```

hackage - https://hackage.haskell.org/package/hext-0.1.0.2