Meta-learning Method for Automatic Selection of Algorithms for Text Classification
نویسندگان
چکیده
The paper presents a meta-learning approach for textual document classification task and an automatic selection of the best available algorithm for creation of classifiers. After brief introductory description of principles of document preprocessing, creation and evaluation of the classifiers, the metalearning approach is presented as a method for automatic selection of the most appropriate classifier algorithm for creation of binary classifiers. Designed method, based on the modification of MUDOF (Metalearning Using Document Feature Characteristics) algorithm, is described together with its implementation using the JBowl Java library. Finally, the experimental results achieved by the metalearning algorithms as well as their comparisons with traditional ways used for text classification are presented.
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