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The dimensions of the feature vectors being used at the classification methods in the literature affect directly the time performance. In this study, how to reduce the dimension of the feature vector by using Turkish's grammar rules without compromising success rates is explained. The feature vector is weighted on the basis of the word frequency as the word(More)
In this study, the impact of term weighting on author detection as a type of text classification is investigated. The feature vector being used to represent texts, consists of stem words as features and their weight values, which are obtained by applying 14 different term weighting schemes. The performances of these feature vectors for 3 different datasets(More)
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