https://github.com/atislabs/scargc.jl

A Julia implementation of Stream Classification Algorithm Guided by Clustering – SCARGC
https://github.com/atislabs/scargc.jl

clustering concept-drift evl julia nonstationary-environments

Last synced: 3 months ago
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A Julia implementation of Stream Classification Algorithm Guided by Clustering – SCARGC

• Host: GitHub
• URL: https://github.com/atislabs/scargc.jl
• Owner: ATISLabs
• License: mit
• Created: 2020-05-05T18:00:15.000Z (about 5 years ago)
• Default Branch: master
• Last Pushed: 2020-09-09T23:30:44.000Z (over 4 years ago)
• Last Synced: 2025-01-22T12:45:50.712Z (5 months ago)
• Topics: clustering, concept-drift, evl, julia, nonstationary-environments
• Language: Jupyter Notebook
• Homepage:
• Size: 14.1 MB
• Stars: 3
• Watchers: 5
• Forks: 0
• Open Issues: 6
• Metadata Files:
  • Readme: README.md
  • License: LICENSE

Awesome Lists containing this project

README

        
# SCARGC.jl

A Julia implementation of **S**tream **C**lassification **A**lgo**r**ithm **G**uided by **C**lustering – **SCARGC** -, an algorithm to classify data streams in nonstationary environments with extreme verification latency. The considered scenario is the one where the actual labels of unlabeled data are never available as a guidance to update the classification model over time.

Documentation | Build

------------- | ----- 

[![](https://img.shields.io/badge/docs-dev-blue.svg)](https://ATISLabs.github.io/SCARGC.jl/dev) | [![Build Status](https://travis-ci.com/ATISLabs/SCARGC.jl.svg?branch=master)](https://travis-ci.com/ATISLabs/SCARGC.jl) [![Coverage Status](https://coveralls.io/repos/github/MarinhoGabriel/SCARGC.jl/badge.svg?branch=master)](https://coveralls.io/github/MarinhoGabriel/SCARGC.jl?branch=master) [![codecov](https://codecov.io/gh/ATISLabs/SCARGC.jl/branch/master/graph/badge.svg)](https://codecov.io/gh/ATISLabs/SCARGC.jl)

## Installation

In Julia terminal, you can use

```julia

using Pkg

Pkg.add("SCARGC")

```

or, if you prefer, you can use the Julia REPL

```julia-repl

(@v1.4)> add SCARGC

```

## Comparison

Between the Julia implementation of SCARGC and the original one, implemented in MatLab, the results were pretty good.

The following picture shows the comparison between SCARGC.jl (in black) and SCARGC.

![Result](results/result.jpeg)

## References

- Stream Classification Algorithm Guided by Clustering - SCARGC

  - [Souza, V. M. A.; Silva, D. F.; Gama, J.; Batista, G. E. A. P. A.: **Data Stream Classification Guided by Clustering on Nonstationary Environments and Extreme Verification Latency**. SIAM International Conference on Data Mining (SDM), pp. 873-881, 2015](https://repositorio.inesctec.pt/bitstream/123456789/5325/1/P-00K-AN4.pdf)

[docs-stable-img]: https://img.shields.io/badge/docs-stable-blue.svg

[docs-stable-url]: https://