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Features extracted from this dataset were used to train and evaluate classification algorithms including decision tree, na\u00efve Bayes, random forest and support vector machine implemented in Weka, an open\u2010source machine learning platform. The best performing classifiers were also tested on a collection of 30,000 names extracted from the UNT Digital Library This poster presents the feature sets, their testing results and the information gains of extracted features. 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