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Naive Bayesian Classification for Golang

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13 reviews
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4.2
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Naive Bayesian Classification for Golang Reviews

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JS
Jayant S.
03/09/2022
Validated Reviewer
Review source: G2 invite
Incentivized Review

Simple to Classify The Text in Programming Way

Ability to classify the text and set the programmatic output for desired business results in an effective manner
Shanika P.
SP
Shanika P.
Associate CI/CD Engineer at Wiley Global Technology (Private) Limited
05/30/2019
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Verified Current User
Review source: G2 invite
Incentivized Review

Got the job done!

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.
Sina J.
SJ
Sina J.
-
09/12/2018
Validated Reviewer
Verified Current User
Review source: Seller invite

A minimalist product to just use it.

I think its title just talks about the product. a light-weighted library to use your classification tasks with the naive-Bayes method. The method is pretty much efficient and fast and the results are accurate. There is not lots of functionality and it is a good thing. you can just do what the code promised you. naive-Bayes classification.

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What is Naive Bayesian Classification for Golang?

Naive Bayesian Classification for Golang, available at https://github.com/jbrukh/bayesian, is an open-source implementation of the Naive Bayes classifier in the Go programming language. This library allows developers to apply statistical classification techniques to categorize data based on Bayes' Theorem. It supports text categorization and uses the assumption that the presence of a particular feature in a class is independent of the presence of any other feature, given the class variable. The project is suitable for tasks such as spam detection, sentiment analysis, and other classification problems. The repository includes documentation and example code to help users integrate the classifier into their Go applications effectively.

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github.com