Naive Bayesian Classification for Golang

What do you like best?

As mentioned in the title, Naive Bayes is a very simple classification algorithm that makes some strong assumptions about the independence of each input variable. I found this when I was searching for a classification algorithm for my research project. It is a light weighted library to use with the Naive Bayes classification algorithm. It was very difficult to find this library for Go language but with the help of this, I got the job done very easily. The method is efficient in its work and the results are accurate as well.

What do you dislike?

In my opinion, I think this needs to improve its documentation a bit more. The current documentation is a bit harder to understand for a beginner like myself.

Recommendations to others considering the product:

I highly recommend this if you're searching for effective and efficient text classification.

What problems are you solving with the product? What benefits have you realized?

As mentioned above, I'm using this product for text classification problems in my research project. This works well with simple classification problems as well as TF-IDF classification.