MIDAS
This is an implementation of MIDAS - edge stream anomaly detection but implemented in Go.
For more information about how it works, please checkout the resources section.
Usage and installation
Checkout the examples folder for detailed instructions
import (
"github.com/steve0hh/midas"
"fmt"
)
func main () {
src := []int{2,2,3,3,5,5,7,11,1,2}
dst := []int{3,3,4,4,9,9,73,74,75,76}
times := []int{1,1,2,2,2,2,2,2,2,2}
// using function to score the edges
midasAnormScore := midas.Midas(src, dst, times, 2, 769)
midasRAnormScore := midas.MidasR(src, dst, times, 2, 769, 0.6)
fmt.Println(midasAnormScore)
fmt.Println(midasRAnormScore)
// using sklearn FitPredict api for midas
m := midas.NewMidasModel(2, 769, 9460)
fmt.Println(m.FitPredict(2,3,1))
fmt.Println(m.FitPredict(2,3,1))
fmt.Println(m.FitPredict(3,4,2))
// using sklearn FitPredict api for midasR
mr := midas.NewMidasRModel(2, 769, 9460, 0.6)
fmt.Println(mr.FitPredict(2,3,1))
fmt.Println(mr.FitPredict(2,3,1))
fmt.Println(mr.FitPredict(3,4,2))
}Resources
- Orginal implementation of MIDAS in C++
- MIDAS: Microcluster-Based Detector of Anomalies in Edge Streams
Citation
If you use this code for your research, please consider citing the original paper.
@article{bhatia2019midas,
title={MIDAS: Microcluster-Based Detector of Anomalies in Edge Streams},
author={Bhatia, Siddharth and Hooi, Bryan and Yoon, Minji and Shin, Kijung and Faloutsos, Christos},
journal={arXiv preprint arXiv:1911.04464},
year={2019}
}
Contributing
Everyone is encouraged to help improve this project. Here are a few ways you can help:
- Report bugs
- Fix bugs and submit pull requests
- Write, clarify, or fix documentation
- Suggest or add new features
TODOs
- Godocs documentation
- Add sklearn/keras fit & predict API
- More examples and tests
- Make code more efficient