There are two well-known characteristics about text classification. One is that the dimension of the sample space is very high, while the number of examples available usually is very small. The other is that the examp...There are two well-known characteristics about text classification. One is that the dimension of the sample space is very high, while the number of examples available usually is very small. The other is that the example vectors are sparse. Meanwhile, we find existing support vector machines active learning approaches are subject to the influence of outliers. Based on these observations, this paper presents a new hybr/d active learning approach. In this approach, to select the unlabelled example(s) to query, the learner takes into account both sparseness and high-dimension characteristics of examples as well as its uncertainty about the examples' categorization. This way, the active learner needs less labeled examples, but still can get a good generalization performance more quickly than competing methods. Our empirical results indicate that this new approach is effective.展开更多
为解决本科生课堂教学普遍存在的学习低效问题,课题组基于"主动学习策略",以管理与沟通技巧课程为试点进行课程教学改革。以Fink L D的综合性课程设计模式框架设计改革方案,分析情境因素,确定学习目标、教学评估和教学活动的...为解决本科生课堂教学普遍存在的学习低效问题,课题组基于"主动学习策略",以管理与沟通技巧课程为试点进行课程教学改革。以Fink L D的综合性课程设计模式框架设计改革方案,分析情境因素,确定学习目标、教学评估和教学活动的内容。课题组评估教学前后在反应层、学习层和行为层的变化,为改进本科生课堂教学提供参考。展开更多
文摘There are two well-known characteristics about text classification. One is that the dimension of the sample space is very high, while the number of examples available usually is very small. The other is that the example vectors are sparse. Meanwhile, we find existing support vector machines active learning approaches are subject to the influence of outliers. Based on these observations, this paper presents a new hybr/d active learning approach. In this approach, to select the unlabelled example(s) to query, the learner takes into account both sparseness and high-dimension characteristics of examples as well as its uncertainty about the examples' categorization. This way, the active learner needs less labeled examples, but still can get a good generalization performance more quickly than competing methods. Our empirical results indicate that this new approach is effective.
文摘针对当前主动学习策略直接用于SVM(Support Vector Machine)分类器时存在的泛化能力不强的问题,提出的两层协同主动学习策略TLCALS(Two-Level Collaboration Active Learning Strategy)应用了协同训练的思想,能深层挖掘未标记样本数据的分布知识。实验表明,TLCALS策略能够合理指定TSVM(Transducive Support Vector Machine)算法中的正样本数,在典型指标测试中都表现出了一定的优越性。
文摘为解决本科生课堂教学普遍存在的学习低效问题,课题组基于"主动学习策略",以管理与沟通技巧课程为试点进行课程教学改革。以Fink L D的综合性课程设计模式框架设计改革方案,分析情境因素,确定学习目标、教学评估和教学活动的内容。课题组评估教学前后在反应层、学习层和行为层的变化,为改进本科生课堂教学提供参考。
