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CCM: Controlling the Change Magnitude in High Dimensional Data

  • Cesare Alippi
  • Giacomo Boracchi
  • Diego CarreraEmail author
Conference paper
Part of the Advances in Intelligent Systems and Computing book series (AISC, volume 529)

Abstract

The effectiveness of change-detection algorithms is often assessed on real-world datasets by injecting synthetically generated changes. Typically, the magnitude of the introduced changes is not controlled, and most of experimental practices lead to results that are difficult to reproduce and compare with. This problem becomes particularly relevant when the data-dimension scales, as it happens in big data applications.

To enable a fair comparison among change-detection algorithms, we have designed “Controlling Change Magnitude” (CCM), a rigorous method to introduce changes in multivariate datasets. In particular, we measure the change magnitude as the symmetric Kullback-Leibler divergence between the pre- and post-change distributions, and introduce changes by applying a roto-translation directly to the data. We present an algorithm to identify the parameters yielding the desired change magnitude, and analytically prove its convergence. Our experiments show the effectiveness of the proposed method and the limitations of tests run on high-dimensional datasets when changes are injected following traditional approaches. The MATLAB framework implementing the proposed method is made publicly available for download.

Keywords

Bisection Method Change Magnitude Realistic Monitoring Multivariate Dataset Popular Machine Learning 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

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Copyright information

© Springer International Publishing AG 2017

Authors and Affiliations

  • Cesare Alippi
    • 1
    • 2
  • Giacomo Boracchi
    • 1
  • Diego Carrera
    • 1
    Email author
  1. 1.Dipartimento di Elettronica, Informazione e Bioingegneria, Politecnico di MilanoMilanoItaly
  2. 2.Università della Svizzera ItalianaLuganoSwitzerland

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