A Comparison of Machine Learning Classification Algorithms and Methods for English Author's Works and their Translations into Bulgarian

The aim of the publication is to compare the accuracy, precision, sensitivity and F-measure of machine algorithms trained in the classification of authors of works by English authors and the classification of authors of the same works translated into Bulgarian. The algorithms examined are Multinomial Naive Bayes classifier, Bernoulli Naive Bayes classifier, Support Vector Machines, Random Forest, AdaBoost, Decision Tree and K-Nearest Neighbosr. The research results show that in the English author's classification with an equal number of works in English, Support Vector Machines and Multinomial Naive Bayes classifier receive the highest values of the studied indicators. In Bulgarian texts, the best results are obtained depending on specific authors.