Genetic Optimization of Keyword Subsets in the Classification Analysis of Authorship of Texts

The genetic selection of keyword sets, the text frequencies of which are considered as attributes in text classification analysis, has been analysed. The genetic optimization was performed on a set of words, which is the fraction of the frequency dictionary with given frequency limits. The frequency dictionary was formed on the basis of an analysed text array of texts of English fiction. As the fitness function which is minimized by the genetic algorithm, the error of the nearest k neighbours classifier was used. The results obtained show high precision and recall of text classification by authorship categories on the basis of attributes of the keyword sets which were selected by the genetic algorithm from the frequency dictionary.