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ANALYSIS OF NURSING-CARE FREESTYLE JAPANESE TEXTCLASSIFICATION USING GA-BASED TERM SELECTION

机译:使用基于GA的术语选择分析护理自由式日语教学

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In this paper, classification performance of a term selection based on GA is analyzed. In the term selection based on GA, two objectives which are maximizing correctly classified texts and minimizing selected terms are optimized. An objective function based on the classification per-formance of the SVM with 10-fold cross validation is used for evaluating each individual in GA. Therefore, GA-based term selection is performed aiming at the improvement in classification per-formance on testing text sets. This causes the performance deterioration over unseen texts in actual use by GA-based term selection because terms are deleted excessively even when such terms have important role for the classification. In this paper, relation between the terms deleted by the term se-lection based on GA and the terms which appears in unseen texts is clarified by numerical simulation results.
机译:本文分析了基于GA的术语选择的分类性能。在基于GA的术语选择中,优化了最大化正确分类和最小化所选术语的两个目标。基于具有10倍交叉验证的SVM分类的目标函数用于评估GA中的每个单独的单个。因此,针对基于GA的术语选择,旨在改善测试文本集上的分类。这导致基于GA的术语选择实际使用中看不见的文本的性能恶化,因为即使这些术语对分类具有重要作用,术语也会过度删除。在本文中,通过数值模拟结果阐明了基于GA的术语SE-Zection删除的术语与看不见的文本中出现的术语之间的关系。

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