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Mining Specification Parameters for Multi-class Classification

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Runtime Verification (RV 2023)

Part of the book series: Lecture Notes in Computer Science ((LNCS,volume 14245))

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Abstract

We present a method for mining parameters of temporal specifications for signal classification. Given a parametric formula and a set of labeled traces, we find one parameter valuation for each class and use it to instantiate the specification template. The resulting formula characterizes the signals in a class by discriminating them from signals of other classes. We propose a two-step approach: first, for each class, we approximate its validity domain, which is the region of the valuations that render the formula satisfied. Second, we select from each validity domain the valuation that maximizes the distance from the validity domain of other classes. We provide a statistical guarantee that the selected parameter valuation is at a bounded distance from being optimal. Finally, we validate our approach on three case studies from different application domains.

This work has received funding from the European Union’s Horizon 2020 research and innovation programme under grant agreement No 956123 and it is partially funded by the TU Wien-funded Doctoral College for SecInt: Secure and Intelligent Human-Centric Digital Technologies.

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Notes

  1. 1.

    https://github.com/eleonoranesterini/MiniPaSTeL.

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Authors and Affiliations

  1. AIT Austrian Institute of Technology, Vienna, Austria

    Edgar A. Aguilar, Cristinel Mateis, Eleonora Nesterini & Dejan Ničković

  2. TU Wien, Vienna, Austria

    Ezio Bartocci & Eleonora Nesterini

Authors
  1. Edgar A. Aguilar
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  2. Ezio Bartocci
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  3. Cristinel Mateis
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  4. Eleonora Nesterini
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  5. Dejan Ničković
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Corresponding author

Correspondence to Eleonora Nesterini .

Editor information

Editors and Affiliations

  1. Dept. of Informatics, Aristotle Univ. of Thessaloniki, Thessaloniki, Greece

    Panagiotis Katsaros

  2. University of Trieste, Trieste, Italy

    Laura Nenzi

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Aguilar, E.A., Bartocci, E., Mateis, C., Nesterini, E., Ničković, D. (2023). Mining Specification Parameters for Multi-class Classification. In: Katsaros, P., Nenzi, L. (eds) Runtime Verification. RV 2023. Lecture Notes in Computer Science, vol 14245. Springer, Cham. https://doi.org/10.1007/978-3-031-44267-4_5

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  • DOI: https://doi.org/10.1007/978-3-031-44267-4_5

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