Author Verification: Exploring a Large set of Parameters using a Genetic Algorithm - Notebook for PAN at CLEF 2014
Résumé
In this paper we present the system we submitted to the PAN'14 competition for the author verification task. We consider the task as a supervised classification problem, where each case in a dataset is an instance. Our system works by applying the same combination of parameters to every case in a dataset. Thus, the training stage consists in finding an optimal combination of parameters which maximizes the performance on the training data using cross-validation. This is achieved using a simple genetic algorithm, since the space of all possible combinations is impractical.
Domaines
Traitement du texte et du document
Origine : Fichiers produits par l'(les) auteur(s)
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