Abstract
This work evaluates and compares different supervised learning algorithms using a costsensitive approach to find a model that classifies legal rules related to pesticides as prohibitions and permissions. The naive Bayes classifier achieves the best results and it would be applicable because it doesn't misclassify prohibitions as permissions.
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