DSO_Sample: Sampling from a Data Stream (Data Stream Operator)
Description
Extracts a sample form a data stream using Reservoir Sampling.
Usage
DSO_Sample(k = 100, biased = FALSE)
Arguments
k
the number of points to be sampled from the stream.
biased
if FALSE then a regular (unbiased)
reservoir sampling is used. If true then
the sample is biased towards keeping more recent data points
(see Details section).
Value
An object of class DSO_Sample (subclass of
DSO).
Details
If biased=FALSE then the reservoir sampling algorithm by McLeod
and Bellhouse (1983) is used. This sampling makes sure that each
data point has the same chance to be sampled. All sampled points
will have a weight of 1. Note that this might not be ideal for an evolving
stream since very old data points have the same chance to be in the sample
as newer points.
If bias=TRUE then sampling prefers newer points using the modified
reservoir sampling algorithm 2.1 by Aggarwal (2006). New points are always
added. They replace a random point in thre reservoir with a probability
of reservoir size over k. This an exponential bias function of
\(2^{-lambda}\) with \(lambda=1/k\).
References
Vitter, J. S. (1985): Random sampling with a reservoir. ACM Transactions
on Mathematical Software, 11(1), 37-57.
McLeod, A.I., Bellhouse, D.R. (1983): A Convenient Algorithm for Drawing a Simple Random Sample. Applied Statistics, 32(2), 182-184.
Aggarwal C. (2006) On Biased Reservoir Sampling in the Presence of Stream Evolution. International Conference on Very Large Databases (VLDB'06). 607-618.