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Description
  • Vyvinuli jsme algoritmus, který odhaduje pokrytí klauzule, tj. počet příkladů, které jsou klauzulí implikovány. Algoritmus je implementován a testován na vygenerovaných i realných datových sadách. (cs)
  • In relational learning, {$\theta$}-subsumption and OI-subsumption are widely used coverage tests. Unfortunately, testing both {$\theta$}-subsumption and OI-subsumption is NP-complete, which is one of the reasons for poor performance of most relational learners. In this paper, we aim at a possible exploitation of randomized restarted search strategies for coverage estimation. We devise an algorithm that can, under a distributional assumption, estimate coverage between a given hypothesis and a set of examples without having to decide the subsumption test for all examples. We implement this algorithm in programs {\sc ReCovEr} and {\sc ReCovErOI}. On artificial graph data and real-world datasets, we show that these algorithms can provide reasonably accurate estimates while achieving favorable runtimes as compared to state-of-the-art algorithms.
  • In relational learning, {$\theta$}-subsumption and OI-subsumption are widely used coverage tests. Unfortunately, testing both {$\theta$}-subsumption and OI-subsumption is NP-complete, which is one of the reasons for poor performance of most relational learners. In this paper, we aim at a possible exploitation of randomized restarted search strategies for coverage estimation. We devise an algorithm that can, under a distributional assumption, estimate coverage between a given hypothesis and a set of examples without having to decide the subsumption test for all examples. We implement this algorithm in programs {\sc ReCovEr} and {\sc ReCovErOI}. On artificial graph data and real-world datasets, we show that these algorithms can provide reasonably accurate estimates while achieving favorable runtimes as compared to state-of-the-art algorithms. (en)
Title
  • Fast Estimation of First Order Clause Coverage through Randomization and Maximum Likelihood
  • Fast Estimation of First Order Clause Coverage through Randomization and Maximum Likelihood (en)
  • Rychlý odhad pokrytí klauzule prostřednictvím randomizace a maximální věrohodnosti (cs)
skos:prefLabel
  • Fast Estimation of First Order Clause Coverage through Randomization and Maximum Likelihood
  • Fast Estimation of First Order Clause Coverage through Randomization and Maximum Likelihood (en)
  • Rychlý odhad pokrytí klauzule prostřednictvím randomizace a maximální věrohodnosti (cs)
skos:notation
  • RIV/68407700:21230/08:03145218!RIV09-GA0-21230___
http://linked.open...avai/riv/aktivita
http://linked.open...avai/riv/aktivity
  • P(GA201/08/0509)
http://linked.open...vai/riv/dodaniDat
http://linked.open...aciTvurceVysledku
http://linked.open.../riv/druhVysledku
http://linked.open...iv/duvernostUdaju
http://linked.open...titaPredkladatele
http://linked.open...dnocenehoVysledku
  • 367691
http://linked.open...ai/riv/idVysledku
  • RIV/68407700:21230/08:03145218
http://linked.open...riv/jazykVysledku
http://linked.open.../riv/klicovaSlova
  • clause coverage; randomization; relational learning (en)
http://linked.open.../riv/klicoveSlovo
http://linked.open...ontrolniKodProRIV
  • [12173B0327ED]
http://linked.open...v/mistoKonaniAkce
  • Helsinki
http://linked.open...i/riv/mistoVydani
  • Madison
http://linked.open...i/riv/nazevZdroje
  • Proceedings of the 25th International Conference on Machine Learning
http://linked.open...in/vavai/riv/obor
http://linked.open...ichTvurcuVysledku
http://linked.open...cetTvurcuVysledku
http://linked.open...vavai/riv/projekt
http://linked.open...UplatneniVysledku
http://linked.open...iv/tvurceVysledku
  • Kuželka, Ondřej
  • Železný, Filip
http://linked.open...vavai/riv/typAkce
http://linked.open.../riv/zahajeniAkce
number of pages
http://purl.org/ne...btex#hasPublisher
  • Omnipress
https://schema.org/isbn
  • 978-1-60558-205-4
http://localhost/t...ganizacniJednotka
  • 21230
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