Modeling position specificity in sequence kernels by fuzzy equivalence relations

Ulrich Bodenhofer, Karin Schwarzbauer, Mihaela Ionescu, Sepp Hochreiter

Research output: Chapter in Book/Report/Conference proceedingConference proceedingspeer-review

Abstract

This paper demonstrates that several known sequence kernels can be expressed in a unified framework in which the position specificity is modeled by fuzzy equivalence relations. In addition to this interpretation, we address the practical issues of positive semidefiniteness, computational complexity, and the extraction of interpretable features from the final support vector machine classifier.
Original languageEnglish
Title of host publicationProc. Joint 13th IFSA World Congress and 6th EUSFLAT Conference
Number of pages6
Publication statusPublished - 2009

Fields of science

  • 101004 Biomathematics
  • 101027 Dynamical systems
  • 101028 Mathematical modelling
  • 101029 Mathematical statistics
  • 101014 Numerical mathematics
  • 101015 Operations research
  • 101016 Optimisation
  • 101017 Game theory
  • 101018 Statistics
  • 101019 Stochastics
  • 101024 Probability theory
  • 101026 Time series analysis
  • 102 Computer Sciences
  • 102001 Artificial intelligence
  • 102003 Image processing
  • 102004 Bioinformatics
  • 102013 Human-computer interaction
  • 102018 Artificial neural networks
  • 102019 Machine learning
  • 103029 Statistical physics
  • 106005 Bioinformatics
  • 106007 Biostatistics
  • 202017 Embedded systems
  • 202035 Robotics
  • 202036 Sensor systems
  • 202037 Signal processing
  • 305901 Computer-aided diagnosis and therapy
  • 305905 Medical informatics
  • 305907 Medical statistics
  • 102032 Computational intelligence
  • 102033 Data mining
  • 101031 Approximation theory

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