We consider the stylometric uses of a pattern recognition technique inspired by neurological research known as neural computation. This involves the training of so-called neural networks to classify data even in the presence of noise and non-linear interactions within data sets. We provide an introduction to this technique, and show how to tailor it to the needs of stylometry. Specifically, we show how to construct so-called multi-layer perceptron neural networks to investigate questions surrounding purported works of Shakespeare and Fletcher. The Double Falsehood and The London Prodigal are found to have strongly Fletcherian characteristics, Henry VIII strongly Shakespearian characteristics, and The Two Noble Kinsmen characteristics suggestive of collaboration.

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