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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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Juan David O.
JO
Juan David O.
Software Test Automation Engineer en EPAM Anywhere
08/05/2022
Validated Reviewer
Review source: G2 invite
Incentivized Review

Great software that serves its purpose

It made it extremely easy to classify and reliable a large dataset performantly. It's a lightweight library to use with the Naive Bayes classification algorithm, with their documentation is easy to get started if you're an experienced engineer and classify your data right away.
Vibhu M.
VM
Vibhu M.
Software Engineer
08/03/2022
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Review source: G2 invite
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Naive Bayesian Classification for Golang Review

Naive Bayes is a strong classification algorithm, arguably one of the most powerful (and popular) algorithm used in Data Science. It was very difficult to find a library for Naive Bayes in Golang, but this got the job! It's light-weight, efficient and though it doesn't have a lot of functionality, it gets the job done.
Hritesh Kumar P.
HP
Hritesh Kumar P.
Associate Software Engineer @Hexaware
07/31/2022
Validated Reviewer
Review source: G2 invite
Incentivized Review

Review for Naive Bayesian classification using golang

The naive bayes algorithm is very usefull for Natural Language processing and the one thing i like the most is the accuracy and fast performance.

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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