Méthode du goulot d'étranglement de l'information

Définition

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Information bottleneck method The information bottleneck method is a technique in information theory introduced by Naftali Tishby, Fernando C. Pereira, and William Bialek.[1] It is designed for finding the best tradeoff between accuracy and complexity (compression) when summarizing (e.g. clustering) a random variable X, given a joint probability distribution p(X,Y) between X and an observed relevant variable Y - and described as providing "a surprisingly rich framework for discussing a variety of problems in signal processing and learning".[1]

Source : Wikipedia Machine Learning