CSlideCluster {funtimes}

Slide-Level Time Series Clustering

Description

Cluster time series at a slide level, based on Algorithm 1 of Ciampi et al. (2010).

Usage

CSlideCluster(X, Alpha = NULL, Beta = NULL, Delta = NULL, Theta = 0.8)

Arguments

X

a matrix of time series observed within a slide (time series in columns).

Alpha

lower limit of the time series domain. Default is quantile(X)[2] -
1.5*(quantile(X)[4] - quantile(X)[2]).

Beta

upper limit of the time series domain. Default is quantile(X)[2] +
1.5*(quantile(X)[4] - quantile(X)[2]).

Delta

closeness parameter, a real value in [0,1]. Default is 0.1*(Beta - Alpha).

Theta

connectivity parameter, a real value in [0,1]. Default is 0.8.

Value

A vector of length ncol(X) with cluster labels.

Author(s)

Vyacheslav Lyubchich

References

Ciampi A, Appice A, Malerba D (2010). “Discovering trend-based clusters in spatially distributed data streams.” In International Workshop of Mining Ubiquitous and Social Environments, 107–122.

See Also

CSlideCluster, CWindowCluster, and BICC

Examples

set.seed(123)
X <- matrix(rnorm(50), 10, 5)
CSlideCluster(X)