Classifying Words with 3-sort Automata
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arXiv
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| Auteurs principaux: | , , |
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| Format: | Preprint |
| Publié: |
2024
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| _version_ | 1866916079748513792 |
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| author | Jastrząb, Tomasz Lardeux, Frédéric Monfroy, Eric |
| author_facet | Jastrząb, Tomasz Lardeux, Frédéric Monfroy, Eric |
| contents | Grammatical inference consists in learning a language or a grammar from data. In this paper, we consider a number of models for inferring a non-deterministic finite automaton (NFA) with 3 sorts of states, that must accept some words, and reject some other words from a given sample. We then propose a transformation from this 3-sort NFA into weighted-frequency and probabilistic NFA, and we apply the latter to a classification task. The experimental evaluation of our approach shows that the probabilistic NFAs can be successfully applied for classification tasks on both real-life and superficial benchmark data sets. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2401_01314 |
| institution | arXiv |
| publishDate | 2024 |
| record_format | arxiv |
| spellingShingle | Classifying Words with 3-sort Automata Jastrząb, Tomasz Lardeux, Frédéric Monfroy, Eric Formal Languages and Automata Theory Grammatical inference consists in learning a language or a grammar from data. In this paper, we consider a number of models for inferring a non-deterministic finite automaton (NFA) with 3 sorts of states, that must accept some words, and reject some other words from a given sample. We then propose a transformation from this 3-sort NFA into weighted-frequency and probabilistic NFA, and we apply the latter to a classification task. The experimental evaluation of our approach shows that the probabilistic NFAs can be successfully applied for classification tasks on both real-life and superficial benchmark data sets. |
| title | Classifying Words with 3-sort Automata |
| topic | Formal Languages and Automata Theory |
| url | https://arxiv.org/abs/2401.01314 |