shield
CloudForest
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| shield | CloudForest | |
|---|---|---|
| 0 | 4 | |
| 154 | 728 | |
| - | - | |
| 0.0 | 0.0 | |
| over 3 years ago | over 1 year ago | |
| Go | Go | |
| MIT License | GNU General Public License v3.0 or later |
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CloudForest
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Trinary Decision Trees for missing value handling
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.
I've got a ~10 year old implementation that does something similar calling it "three way splitting" here: https://github.com/ryanbressler/CloudForest
And i got the idea from a lab mate, Timo Erkkila's RF-ACE project though neither of us thought it was a particularly novel idea.
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[D] Best methods for imbalanced multi-class classification with high dimensional, sparse predictors
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?
Gorgonia - Gorgonia is a library that helps facilitate machine learning in Go.
libsvm - libsvm go version
gago - :four_leaf_clover: Evolutionary optimization library for Go (genetic algorithm, partical swarm optimization, differential evolution)
EAGO
go-deep - Artificial Neural Network
gobrain - Neural Networks written in go
tfgo - Tensorflow + Go, the gopher way
go-galib - Genetic Algorithms library written in Go / golang
GoLearn - Machine Learning for Go
goga - Golang Genetic Algorithm