Introducing G2.ai, the future of software buying.Try now
Product Avatar Image

Naive Bayesian Classification for Golang

Show rating breakdown
13 reviews
  • 1 profiles
  • 1 categories
Average star rating
4.2
Serving customers since

Profile Name

Star Rating

8
4
1
0
0

Naive Bayesian Classification for Golang Reviews

Review Filters
Profile Name
Star Rating
8
4
1
0
0
Abdellah A.
AA
Abdellah A.
Social Entrepreneur | Youth Leadership Award | TEDx Speaker | Global Shaper at World Economic Forum
10/14/2024
Validated Reviewer
Review source: G2 invite
Incentivized Review

I worked with Naive Bayesian as part of my project in my company, I believe it served us fairly.

Working in a specific projects can be hard to manipulate the entire process, I believe it would be nice to customize the outcomes.
Harshal M.
HM
Harshal M.
Work at Havells India ltd
02/03/2023
Validated Reviewer
Verified Current User
Review source: G2 invite
Incentivized Review

Trigger and Apex class

Naive bayesiqn algorithm is supervise learning algorithm which is base on Bayes thearom
Gyanendra S.
GS
Gyanendra S.
I Regulatory affairs I Pharmaceutical I CMC Scientist I Lifecycle management I PA Change I NDA I Generic drugs
01/13/2023
Validated Reviewer
Review source: G2 invite
Incentivized Review

Excellent tools

Everything was so good. It's more use full for any body it's it's totally as per expectation and all the classification model is according to the requirements.

About

Contact

HQ Location:
New York City, NY

Social

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.

Details

Website
github.com