1. Classifying Words with 3-sort Automata
- Author
-
Jastrząb, Tomasz, Lardeux, Frédéric, and Monfroy, Eric
- Subjects
Computer Science - Formal Languages and Automata Theory - Abstract
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.
- Published
- 2024