https://github.com/made2591/go-cpt
A Go implementation of Compact Prediction Tree. A blog post related is available (see README.md)
https://github.com/made2591/go-cpt
cpt go golang ml prediction sequence unik unikernel
Last synced: 4 months ago
JSON representation
A Go implementation of Compact Prediction Tree. A blog post related is available (see README.md)
- Host: GitHub
- URL: https://github.com/made2591/go-cpt
- Owner: made2591
- License: mit
- Created: 2018-11-19T17:53:18.000Z (over 6 years ago)
- Default Branch: master
- Last Pushed: 2018-12-01T12:02:45.000Z (over 6 years ago)
- Last Synced: 2025-01-13T10:50:14.330Z (5 months ago)
- Topics: cpt, go, golang, ml, prediction, sequence, unik, unikernel
- Language: Go
- Homepage: https://made2591.github.io/blog/compact-prediction-tree
- Size: 2.49 MB
- Stars: 0
- Watchers: 3
- Forks: 0
- Open Issues: 0
-
Metadata Files:
- Readme: README.md
- License: LICENSE
Awesome Lists containing this project
README
# go-cpt
A Go implementation of Compact Prediction Tree. A blog post related is [available](https://made2591.github.io/posts/compact-prediction-tree).
## Instructions
To install:
```
git clone https://github.com/made2591/go-cpt
cd go-cpt
go run main.go
```
## Build UniK image
Assuming you already installed UniK correctly, then with a daemon running in a terminal open another shell and run:
```
unik build --name go-cpt-image --path ./ --base rump --language go --provider virtualbox --force
unik run --instanceName go-cpt-instance --imageName go-cpt-image
```
To retrieve the running instances:
```
unik instances
```
You can see IP assigned to instances in the last column of the output
To see the logs of the running instances run:
```
unik logs --instance go-cpt-instance
```
What this image does is actually expose the different endpoint to initialize training and make prediction by rest api - ```it's only a draft```:
A sample file are already uploaded into the upload folder: you can modify the ```main.go``` root of the project to avoid cutting the training and testing set. Otherwise, to see the run you can both execute the code locally or
```
curl http://:8080/initcpt
```
You should see predictions for the first 10 sequences :-)
## Author
* **Matteo Madeddu** - *[here](https://made2591.github.io) is my github personal page* -
## Credits
- [UniK contributors](https://github.com/solo-io/unik/graphs/contributors)
- [NeerajSarwan](https://github.com/NeerajSarwan)