DSC_Window: A sliding window from a Data Stream

In stream: Infrastructure for Data Stream Mining

A sliding window from a Data Stream

Description

Interface for DSO_Window. Represents the points in the sliding window as micro-clusters.

Usage

DSC_Window(horizon = 100, lambda = 0)

Arguments

horizon	the window length.
lambda	decay factor damped window model. lambda = 0 means no dampening.

Details

If lambda is greater than 0 then the weight uses a damped window model (Zhu and Shasha, 2002). The weight for points in the window follows 2^{-lambda*t} where t is the age of the point.

Value

An object of class DSC_Window (subclass of DSC, DSC_R, DSC_Micro).

Author(s)

Michael Hahsler

References

Zhu, Y. and Shasha, D. (2002). StatStream: Statistical Monitoring of Thousands of Data Streams in Real Time, International Conference of Very Large Data Bases (VLDB'02).

See Also

Other DSC_Micro: DSC_BICO(), DSC_BIRCH(), DSC_DBSTREAM(), DSC_DStream(), DSC_Micro(), DSC_Sample(), DSC_evoStream()

Examples

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

window <- DSC_Window(horizon = 100)
window

update(window, stream, 200)
window

# plot micro-clusters
plot(window, stream)

# animation for a window using a damped window model. The weight decays
# with a half-life of 25
## Not run: 
window <- DSC_Window(horizon = 25, lambda = 1 / 25)
animate_cluster(window, stream, horizon = 1, n = 100, xlim = c(0, 1), ylim = c(0, 1))

## End(Not run)

stream documentation built on May 29, 2024, 9:43 a.m.