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rdf:type
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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)
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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)
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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)
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skos:notation
| - RIV/68407700:21230/08:03145218!RIV09-GA0-21230___
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http://linked.open...avai/riv/aktivita
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http://linked.open...avai/riv/aktivity
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http://linked.open...vai/riv/dodaniDat
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http://linked.open...aciTvurceVysledku
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http://linked.open.../riv/druhVysledku
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http://linked.open...iv/duvernostUdaju
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http://linked.open...titaPredkladatele
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http://linked.open...dnocenehoVysledku
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http://linked.open...ai/riv/idVysledku
| - RIV/68407700:21230/08:03145218
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http://linked.open...riv/jazykVysledku
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http://linked.open.../riv/klicovaSlova
| - clause coverage; randomization; relational learning (en)
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http://linked.open.../riv/klicoveSlovo
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http://linked.open...ontrolniKodProRIV
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http://linked.open...v/mistoKonaniAkce
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http://linked.open...i/riv/mistoVydani
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http://linked.open...i/riv/nazevZdroje
| - Proceedings of the 25th International Conference on Machine Learning
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http://linked.open...in/vavai/riv/obor
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http://linked.open...ichTvurcuVysledku
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http://linked.open...cetTvurcuVysledku
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http://linked.open...vavai/riv/projekt
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http://linked.open...UplatneniVysledku
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http://linked.open...iv/tvurceVysledku
| - Kuželka, Ondřej
- Železný, Filip
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http://linked.open...vavai/riv/typAkce
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http://linked.open.../riv/zahajeniAkce
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number of pages
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http://purl.org/ne...btex#hasPublisher
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https://schema.org/isbn
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http://localhost/t...ganizacniJednotka
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