goRecommend vs ddt

goRecommend

Collaborative Filtering (CF) Algorithms in Go! (by timkaye11)

ddt

Golang Dynamic Decision Tree (by sgrodriguez)

#Machine Learning #Go #Golang #decision-tree #decison-trees #Tree #decision #user-tree

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goRecommend		ddt
	Project
0	Mentions	2
182	Stars	16
-	Growth	-
0.0	Activity	0.0
almost 8 years ago	Latest Commit	over 1 year ago
Go	Language	Go
MIT License	License	MIT License

The number of mentions indicates the total number of mentions that we've tracked plus the number of user suggested alternatives.
Stars - the number of stars that a project has on GitHub. Growth - month over month growth in stars.
Activity is a relative number indicating how actively a project is being developed. Recent commits have higher weight than older ones.
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.

goRecommend

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

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

ddt

Posts with mentions or reviews of ddt. We have used some of these posts to build our list of alternatives and similar projects. The last one was on 2021-05-16.

Ask HN: What are some tools / libraries you built yourself?
264 projects | news.ycombinator.com | 16 May 2021

DDT allows building custom decision trees based in a set of defined rules, programmatically or from json.
When making a decision, it allows adding a pre-processing stage to the input before comparing it with the following possible branches of the tree.
https://github.com/sgrodriguez/ddt
What is your “I don't care if this succeeds” project?
42 projects | news.ycombinator.com | 1 Feb 2021

https://github.com/sgrodriguez/ddt a decision tree lib in golang for building custom rules decision tree. It allows adding a pre-processing stage to the input before comparing it with the following possible branches of the tree. One of the default preprocessing stages in ddt is calling a method of a struct (CallStructMethod) and getting the attribute of a struct (GetStructAttribute) using reflection, so you can have a struct user with some methods and attributes and build a tree asking question about the user.

What are some alternatives?

When comparing goRecommend and ddt you can also consider the following projects:

m2cgen - Transform ML models into a native code (Java, C, Python, Go, JavaScript, Visual Basic, C#, R, PowerShell, PHP, Dart, Haskell, Ruby, F#, Rust) with zero dependencies

shield - Bayesian text classifier with flexible tokenizers and storage backends for Go

onnx-go - onnx-go gives the ability to import a pre-trained neural network within Go without being linked to a framework or library.

Varis - Golang Neural Network

gobrain - Neural Networks written in go

ocrserver - A simple OCR API server, seriously easy to be deployed by Docker, on Heroku as well

Goptuna - A hyperparameter optimization framework, inspired by Optuna.

NEUGO

golinear - liblinear bindings for Go

go-pr - Pattern recognition package in Go lang.

go-deep - Artificial Neural Network

goRecommend vs m2cgen

ddt vs m2cgen