bayesian VS go-featureprocessing

Compare bayesian vs go-featureprocessing and see what are their differences.


Naive Bayesian Classification for Golang. (by jbrukh)


🔥 Fast, simple sklearn-like feature processing for Go (by nikolaydubina)
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bayesian go-featureprocessing
0 6
733 75
- -
0.0 3.7
almost 2 years ago 2 months ago
Go Go
GNU General Public License v3.0 or later MIT License
The number of mentions indicates the total number of mentions that we've tracked plus the number of user suggested alternatives.
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For example, an activity of 9.0 indicates that a project is amongst the top 10% of the most actively developed projects that we are tracking.


Posts with mentions or reviews of bayesian. We have used some of these posts to build our list of alternatives and similar projects.

We haven't tracked posts mentioning bayesian yet.
Tracking mentions began in Dec 2020.


Posts with mentions or reviews of go-featureprocessing. We have used some of these posts to build our list of alternatives and similar projects. The last one was on 2021-04-05.

What are some alternatives?

When comparing bayesian and go-featureprocessing you can also consider the following projects:

GoLearn - Machine Learning for Go

gosseract - Go package for OCR (Optical Character Recognition), by using Tesseract C++ library

Gorgonia - Gorgonia is a library that helps facilitate machine learning in Go.

go-fann - Go bindings for FANN, library for artificial neural networks

gobrain - Neural Networks written in go

neural-go - A multilayer perceptron network implemented in Go, with training via backpropagation.

Goptuna - A hyperparameter optimization framework, inspired by Optuna.

golinear - liblinear bindings for Go

goga - Golang Genetic Algorithm

go-pr - Pattern recognition package in Go lang.

go-galib - Genetic Algorithms library written in Go / golang

CloudForest - Ensembles of decision trees in go/golang.