A comparative study of machine learning methods for authorship attribution.

We compare and benchmark the performance of five classification methods, four of which are taken from the machine learning literature, in a classic authorship attribution problem involving the Federalist Papers. Cross-validation results are reported for each method, and each method is further employ...

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Detalles Bibliográficos

Publicado en:	Literary & Linguistic Computing Vol. 25; no. 2; pp. 215 - 224
Autores principales:	Jockers, Matthew L., Witten, Daniela M.
Formato:	Artículo
Publicado:	Oxford University Press / USA Jun2010
Materias:	Attribution of authorship Machine learning Artificial intelligence Machine theory Multivariate analysis Statistical correlation
Acceso en línea:	Ver este registro en EBSCOhost