November 2017
Beginner to intermediate
366 pages
7h 59m
English
Content preview from R Data Analysis Projects
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Drift
The second challenge is the non-stationary aspect of the streaming data. Data is considered stationary if its statistical attributes such as mean, standard deviation, and others do not vary over time. However, we cannot make this assumption for streaming data. This non-stationary behavior is also called drift. Our algorithms should be able to spot and handle drifts efficiently.
The paper, Open Challenges for Data Stream Mining Research, by Georg Kremp et. al (http://www.kdd.org/exploration_files/16-1-2014.pdf), clearly classifies the various issues with processing the stream data.
They explain drift in terms of volatility:
- Volatility corresponds to a dynamic environment with ever-changing patterns. Here, old data is of limited use, ...
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