DSC_SinglePass

The abstract class for all single-pass clusterers. Cannot be instantiated. Must be inherited.
Outlier detecting clusterers are usually single-pass clusterers, since the outlier detection event must be reported as soon as possible back to the caller.

DSC_SinglePass-class

A framework for data stream modeling and associated data mining tasks such as clustering and classification. The development of this package was supported in part by NSF IIS-0948893 and NIH R21HG005912. Hahsler et al (2017) <doi:10.18637/jss.v076.i14>.

Michael Hahsler

stream

Infrastructure for Data Stream Mining

Matthew Bolanos

John Forrest

Matthias Carnein

Dennis Assenmacher

Dalibor Krle<c5><be>a

DSC_SinglePass-class function

<dl class="dl-horizontal">
<dt><code>get_assignments(dsc, points, type=c("auto", "micro", "macro"), method=c("auto", "nn", "model"), ...)</code></dt><dd>A method that needs to be re-implemented by all single-pass clusterers. In this method, each data instance retrieved from an input data stream must be processed in two steps:
<ol>
<li>Classification, which contributes to the returning data frame,</li>
<li>Model update</li>
</ol></dd>
</dl>

Methods

Abstract Class for Single-Pass Clusterers — DSC_SinglePass-class

<dl class='dl-horizontal'>
<dt><code>get_assignments(dsc, points, type=c("auto", "micro", "macro"), method=c("auto", "nn", "model"), ...)</code></dt><dd>A method that needs to be re-implemented by all single-pass clusterers. In this method, each data instance retrieved from an input data stream must be processed in two steps:
<ol>
<li>Classification, which contributes to the returning data frame,</li>
<li>Model update</li>
</ol></dd>
</dl>

DSC_SinglePass-class: Abstract Class for Single-Pass Clusterers

Description

Arguments

Methods