go-galib VS CloudForest

Compare go-galib vs CloudForest and see what are their differences.

go-galib

Genetic Algorithms library written in Go / golang (by thoj)

CloudForest

Ensembles of decision trees in go/golang. (by ryanbressler)
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go-galib CloudForest
- 4
199 735
- -
0.0 0.0
over 8 years ago over 2 years ago
Go Go
- GNU General Public License v3.0 or later
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.

go-galib

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

We haven't tracked posts mentioning go-galib yet.
Tracking mentions began in Dec 2020.

CloudForest

Posts with mentions or reviews of CloudForest. We have used some of these posts to build our list of alternatives and similar projects. The last one was on 2023-09-12.
  • Trinary Decision Trees for missing value handling
    2 projects | news.ycombinator.com | 12 Sep 2023
    I implemented something like this in a [pre xgboost boosting framework](https://github.com/ryanbressler/CloudForest) ~10 years ago and it worked well.

    It isn't even that much of a speed hit using the classical sorting CART implementation. However xgboost and ligthgbm use histogram based approximate sorting which might be harder to adapt in a performant way. And certainly the code will be a lot messier.

  • Future of Golang
    1 project | /r/golang | 22 Sep 2022
    Personally, my Go-to ML tool for tabular data is here: https://github.com/ryanbressler/CloudForest
  • [D] Best methods for imbalanced multi-class classification with high dimensional, sparse predictors
    2 projects | /r/MachineLearning | 19 Jul 2021
    The best method i've seen for dealing with this bias is to create "artificial contrasts" by including possibly many permutated copies of each feature and then doing a statistical test of the random forest importance values for each feature vs its shuffled contrasts. This method is described here: https://www.jmlr.org/papers/volume10/tuv09a/tuv09a.pdf and there is an implementation here: https://github.com/ryanbressler/CloudForest

What are some alternatives?

When comparing go-galib and CloudForest you can also consider the following projects:

gago - :four_leaf_clover: Evolutionary optimization library for Go (genetic algorithm, partical swarm optimization, differential evolution)

libsvm - libsvm go version

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

gobrain - Neural Networks written in go

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

goml - On-line Machine Learning in Go (and so much more)

GoLearn - Machine Learning for Go

go-pr - Pattern recognition package in Go lang.

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

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Get real-time insights from all types of time series data with InfluxDB. Ingest, query, and analyze billions of data points in real-time with unbounded cardinality.
www.influxdata.com
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