Machine learning techniques are based on an explicit or implicit model that enables categorize established patterns analyzed. A unique feature of these schemes is the need to train labeled data model behavior, this being a process that demands resources. Many machine learning-based schemes have been applied to NIDS. Some of the most important are Bayesian networks, Markov models, neural networks, fuzzy logic techniques, genetic algorithms, and clustering and outlier detection (Carbonneau, et. al., 2008, pp. 1140-54). The task of automatic text classification is based on building and using machines called supervised learning. The process of creating an ...