reCluster: re-cluster clustering by 'kmeans'

Description Usage Arguments

View source: R/clusterTools.R

Description

Use cluster centers from an initial clustering to initialize kmeans. This is still experimental, and used to re-associated data rows to cluster centers from a best clustering found by flowclusterTimeseries. While the latter clustering works best to extract specific time-courses from the data set, it often comes with a high fraction of badly associated individual data sets. Re-clustering with kmeans seems to clean this up, e.g., the phase distributions of re-clustered clusterings are often tighter. TODO: allow to generate cluster centers from novel data, to account for different/more data then during clustering!

Usage

1
reCluster(tset, cset, k, select = TRUE, ...)

Arguments

tset

the ‘timeseries’ object from segmenTier's processTimeseries used for initial clustering

cset

the ‘clustering’ object from segmenTier's flowclusterTimeseries

k

colum name or index of the clustering that should be re-clustered; defaults to the pre-selected clustering if missing

select

use the re-clustered clustering as the new pre-selected clustering

...

parameters to kmeans


raim/segmenTools documentation built on Nov. 9, 2018, 5:38 p.m.