Computational Stylistics using Artificial Neural Networks
نویسندگان
چکیده
Previous work in using Artificial Neural Networks for computational stylistics has concentrated on using large, arbitrary network structures. This paper examines the use of the Cascade-Correlation algorithm for the construction of minimal networks. We find that a number of problems in computational stylistics with a large number of variables, but a limited number of training examples may be solved successfully without resorting to large networks. The issue of redundancy in the data is also considered.
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