Dbscan 3.0.0

.NET 6.0 .NET Core 3.1 .NET Standard 1.2
dotnet add package Dbscan --version 3.0.0
NuGet\Install-Package Dbscan -Version 3.0.0
This command is intended to be used within the Package Manager Console in Visual Studio, as it uses the NuGet module's version of Install-Package.
<PackageReference Include="Dbscan" Version="3.0.0" />
For projects that support PackageReference, copy this XML node into the project file to reference the package.
paket add Dbscan --version 3.0.0
#r "nuget: Dbscan, 3.0.0"
#r directive can be used in F# Interactive, C# scripting and .NET Interactive. Copy this into the interactive tool or source code of the script to reference the package.
// Install Dbscan as a Cake Addin
#addin nuget:?package=Dbscan&version=3.0.0

// Install Dbscan as a Cake Tool
#tool nuget:?package=Dbscan&version=3.0.0


This is an implementation of the DBSCAN clustering algorithm in .NET. The primary advantage of this library over other DBSCAN implementations is that this library allows the use of spatial indexes, and is agnostic to the index.

Most implementations of DBSCAN use an O(N) search over every data point to find nearby data points. Sincethis search is executed for every point, the overall clustering time is O(N<sup>2</sup>). This is fine for smaller data sets, but better tools are needed to review larger data sets (say 100,000 points).

If we can provide a better index for searching for nearby data points, then we can reduce the overall time for clustering. For example, using an R-Tree or a K-d tree can reduce time to find neighbors to O(log n), which cuts the overall clustering to O(n log n).

A default spatial index using the above is provided in the primary library as ListSpatialIndex<T>. Alternatively, an R-Tree library is available in the secondary library as RBushSpatialIndex<T>.

Build status License




Install with Nuget:

  • Primary library: Install-Package DBSCAN
  • Secondary library: Install-Package DBSCAN.RBush


Convenience functions have been provided in both libraries. Call the CalculateClusters() function in either DBSCAN or DBSCAN.RBush.

var clusters = Dbscan.CalculateClusters(
    epsilon: 1.0,
    minimumPointsPerCluster: 4);


var clusters = DbscanRBush.CalculateClusters(
    epsilon: 1.0,
    minimumPointsPerCluster: 4);

If you have implemented an alternative ISpatialIndex<T>, then you can provide the index directly to DBSCAN.CalculateClusters():

var clusters = DBSCAN.CalculateClusters(
    epsilon: 1.0,
    minimumPointsPerCluster: 4);


Clone the repository and open DBSCAN.sln in Visual Studio.


DBSCAN should run on any .NET system that supports .NET Standard 1.2 (.NET Framework 4.5.1 or later; .NET Core 1.0 or later).

Product Versions
.NET net5.0 net5.0-windows net6.0 net6.0-android net6.0-ios net6.0-maccatalyst net6.0-macos net6.0-tvos net6.0-windows net7.0 net7.0-android net7.0-ios net7.0-maccatalyst net7.0-macos net7.0-tvos net7.0-windows
.NET Core netcoreapp1.0 netcoreapp1.1 netcoreapp2.0 netcoreapp2.1 netcoreapp2.2 netcoreapp3.0 netcoreapp3.1
.NET Standard netstandard1.2 netstandard1.3 netstandard1.4 netstandard1.5 netstandard1.6 netstandard2.0 netstandard2.1
.NET Framework net451 net452 net46 net461 net462 net463 net47 net471 net472 net48
MonoAndroid monoandroid
MonoMac monomac
MonoTouch monotouch
Tizen tizen30 tizen40 tizen60
Universal Windows Platform uap uap10.0
Windows Phone wpa81
Windows Store netcore451
Xamarin.iOS xamarinios
Xamarin.Mac xamarinmac
Xamarin.TVOS xamarintvos
Xamarin.WatchOS xamarinwatchos
Compatible target framework(s)
Additional computed target framework(s)
Learn more about Target Frameworks and .NET Standard.
  • .NETCoreApp 3.1

    • No dependencies.
  • .NETStandard 1.2

  • net6.0

    • No dependencies.

NuGet packages (2)

Showing the top 2 NuGet packages that depend on Dbscan:

Package Downloads

Boilerplate code to connect RBush with Dbscan.


VL implementation of viceroypenguin's DBSCAN .net library

GitHub repositories

This package is not used by any popular GitHub repositories.

Version Downloads Last updated
3.0.0 988 7/12/2022
2.0.12 33,363 3/12/2018
1.0.10 872 7/13/2017
1.0.9 789 7/13/2017
1.0.2 904 7/13/2017
1.0.1 1,080 7/13/2017