Conversation is one of the basic forms of daily communication,while the research of turn-taking is the central issue in conversation analysis.In class the pragmatic strategies in turn-taking between teachers and stude...Conversation is one of the basic forms of daily communication,while the research of turn-taking is the central issue in conversation analysis.In class the pragmatic strategies in turn-taking between teachers and students are the important interaction abilities.The good use of turn-taking helps students express themselves effectively and enhances the interactive communications successfully.展开更多
β-turn is one of the most important reverse turns because of its role in protein folding. Many computational methods have been studied for predicting β-turns and β-turn types. However, due to the imbalanced dataset...β-turn is one of the most important reverse turns because of its role in protein folding. Many computational methods have been studied for predicting β-turns and β-turn types. However, due to the imbalanced dataset, the performance is still inadequate. In this study, we proposed a novel over-sampling technique FOST to deal with the class-imbalance problem. Experimental results on three standard benchmark datasets showed that our method is comparable with state-of-the-art methods. In addition, we applied our algorithm to five benchmark datasets from UCI Machine Learning Repository and achieved significant improvement in G-mean and Sensitivity. It means that our method is also effective for various imbalanced data other than β-turns and β-turn types.展开更多
文摘Conversation is one of the basic forms of daily communication,while the research of turn-taking is the central issue in conversation analysis.In class the pragmatic strategies in turn-taking between teachers and students are the important interaction abilities.The good use of turn-taking helps students express themselves effectively and enhances the interactive communications successfully.
文摘β-turn is one of the most important reverse turns because of its role in protein folding. Many computational methods have been studied for predicting β-turns and β-turn types. However, due to the imbalanced dataset, the performance is still inadequate. In this study, we proposed a novel over-sampling technique FOST to deal with the class-imbalance problem. Experimental results on three standard benchmark datasets showed that our method is comparable with state-of-the-art methods. In addition, we applied our algorithm to five benchmark datasets from UCI Machine Learning Repository and achieved significant improvement in G-mean and Sensitivity. It means that our method is also effective for various imbalanced data other than β-turns and β-turn types.
