https://github.com/augustocl/clusteranalysis.jl

Cluster Algorithms from Scratch with Julia Lang. (K-Means and DBSCAN)
https://github.com/augustocl/clusteranalysis.jl

algorithms cluster clustering dbscan dbscan-clustering julia k-means k-means-clustering machine-learning

Last synced: about 1 month ago
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Cluster Algorithms from Scratch with Julia Lang. (K-Means and DBSCAN)

• Host: GitHub
• URL: https://github.com/augustocl/clusteranalysis.jl
• Owner: AugustoCL
• License: mit
• Created: 2021-07-29T01:19:50.000Z (over 3 years ago)
• Default Branch: main
• Last Pushed: 2022-11-07T22:06:14.000Z (about 2 years ago)
• Last Synced: 2024-10-27T19:58:12.516Z (about 2 months ago)
• Topics: algorithms, cluster, clustering, dbscan, dbscan-clustering, julia, k-means, k-means-clustering, machine-learning
• Language: Julia
• Homepage: https://augustocl.github.io/ClusterAnalysis.jl/
• Size: 6.3 MB
• Stars: 24
• Watchers: 1
• Forks: 4
• Open Issues: 1
• Metadata Files:
  • Readme: README.md
  • License: LICENSE
  • Citation: CITATION.cff

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README

        
# ClusterAnalysis.jl

[![Stable](https://img.shields.io/badge/docs-stable-blue.svg)](https://AugustoCL.github.io/ClusterAnalysis.jl/stable)

[![Dev](https://img.shields.io/badge/docs-dev-blue.svg)](https://AugustoCL.github.io/ClusterAnalysis.jl/dev)

[![Build Status](https://github.com/AugustoCL/ClusterAnalysis.jl/workflows/CI/badge.svg)](https://github.com/AugustoCL/ClusterAnalysis.jl/actions)

[![Coverage](https://codecov.io/gh/AugustoCL/ClusterAnalysis.jl/branch/main/graph/badge.svg)](https://codecov.io/gh/AugustoCL/ClusterAnalysis.jl)

[![DOI](https://zenodo.org/badge/390558951.svg)](https://zenodo.org/badge/latestdoi/390558951)

  

This package was **built from scratch**, entirely in [Julia Lang](https://julialang.org/), and implements a few popular clustering algorithms like K-Means and DBSCAN. 

This is mostly a learning experiment, but the package were also built and documented to be used by anyone, Plug-and-Play. Just input your data as an Array or a [Tables.jl](https://discourse.julialang.org/t/tables-jl-a-table-interface-for-everyone/14071) type (like [DataFrames.jl](https://dataframes.juliadata.org/stable/)), then start training your clusters algorithms and analyze your results. 

Documentation: [https://augustocl.github.io/ClusterAnalysis.jl/](https://augustocl.github.io/ClusterAnalysis.jl/)

## Algorithms Implemented

Currently we implemented two types of algorithms, a partitioned based ([K-Means](https://en.wikipedia.org/wiki/K-means_clustering)) and a spatial density based ([DBSCAN](https://en.wikipedia.org/wiki/DBSCAN)). 

> Go check the `Algorithms Overview` Section that contains all the details of how it works the algorithm and also got the bibliography and papers used during the research and development of the code.

>It's a great introduction to the algorithm and a good resource to read along with the source code.

- [DBSCAN](https://augustocl.github.io/ClusterAnalysis.jl/stable/algorithms/dbscan/)

- [K-Means](https://augustocl.github.io/ClusterAnalysis.jl/stable/algorithms/kmeans/)

## How to install ClusterAnalysis.jl

```julia

# press ] to enter in Pkg REPL mode.

julia> ]

pkg> add ClusterAnalysis

```  

## To-Do

- [X] Add K-Means++ initialization, to go beyond the random initialization proposed by Andrew NG. DONE

- [X] Create DBSCAN algorithm. DONE

- [ ] Create Hierarchical clustering algorithms with single, complete and average linkage options.