Interface for MOA Stream Clustering Algorithms

Interface for data stream clustering algorithms implemented in the MOA (Massive Online Analysis) framework (Albert Bifet, Geoff Holmes, Richard Kirkby, Bernhard Pfahringer (2010). MOA: Massive Online Analysis, Journal of Machine Learning Research 11: 1601-1604).

R package streamMOA - Interface for MOA Stream Clustering Algorithms

Maintainer: Michael Hahsler

Interface for data stream clustering algorithms implemented in the MOA (Massive Online Analysis) framework. This is an extension package for stream.

Installation

Stable CRAN version: Install from within R with

install.packages("streamMOA")

Current development version: Install from r-universe.

install.packages("streamMOA",
    repos = c("https://mhahsler.r-universe.dev",
              "https://cloud.r-project.org/"))

Example

Create 3 clusters with 5% noise.

library(streamMOA)

stream <- DSD_Gaussians(k = 3, d = 2, noise = 0.05)

Cluster with CluStream.

clustream <- DSC_CluStream(m = 50, k = 3)
update(clustream, stream, 500)
clustream

## CluStream 
## Class: moa/clusterers/clustream/WithKmeans, DSC_MOA, DSC_Micro, DSC 
## Number of micro-clusters: 50 
## Number of macro-clusters: 3

Plot micro-clusters.

plot(clustream, stream)