The experiments on real corpus show that the proposed method can more effectively and stably utilize the unlabeled examples to improve classification generalization.
通过真实语料上进行的比较实验，证明了该方法能有效利用大量未标注语料提高算法的泛化能力。
The new system is flexible and adjustable. The experimental results show that the application of this model improves the classification accuracy and generalization capability of the system.
该系统具有很好的灵活性和可调性，实验表明该模型的应用提高了系统的分类精度，增强了系统的泛化能力。
This approach greatly improves the generalization ability of SVM classification and its application area is extended.
这一方法大大提高了支持向量机分类的泛化能力，从而大大提高了支持向量机的应用范围。
And the accuracy rate of a classification network is explained as the maximum likelihood estimation of the generalization ability.
证明了一个分类网络的测试集正确率是该网络推广能力的极大似然估计；
Ensemble learning is a research hotspot in machine learning, which can improve generalization performance of classification algorithm.
集成学习是当前机器学习的一个研究热点，它可以提高分类算法的泛化性能。
The experiment results show that the proposed approach has the merits of high learning efficiency, high classification accuracy and high generalization capability.
实验结果表明，所提出的方法具有学习效率高、分类准确率高、泛化能力高的优点。
The SVM method is based on seeking on the Structural Risk Minimization by few learning samples supporting, and it has important feature such as good generalization and classification performance, etc.
支持向量机方法基于小学习样本条件下，通过寻求结构风险最小，以期获得良好的分类效果和泛化能力。
The high generalization ability of Support Vector Machine (SVM) makes it especially suitable for the classification of high-dimension data such as term-document.
支持向量机(SVM)高度的泛化能力使它特别适用于高维数据例如文档的分类。
Expatiating on Lewis acids and bases of generalization, Hard and Soft of acids and bases reaction rule, classification, scaling of HSAB and its explanation of theory.
阐述离子和化合物的广义酸碱分类，软硬酸碱反应规则，软硬酸碱的硬度定量标度和理论解释。
Kernel-based Support Vector Machine (SVM) is widely used in many fields (e. g. image classification) for its good generalization, in which the key factor is to design effective kernel functions.
基于核方法的支持向量机(SVM)以其良好的推广性在图像分类等领域已经得到广泛应用，运用支持向量机的关键是设计有效的核函数。
The fundamental issue for classification problem caring about is how to effectively improve the generalization ability of the classification system.
分类所关心的一个根本问题是如何有效地提高分类系统的泛化能力。
The implementation shows that the method has a good classification accuracy and generalization capability.
实验结果表明该方法具有很高的分类和泛化能力。
Data Mining mainly studies on research Generalization Knowledge, Association Knowledge, Classification Knowledge, Clustering Knowledge, Prediction Knowledge, and Deviation Knowledge.
数据挖掘主要研究内容包括广义知识、关联知识、分类知识、聚类知识、预测型知识和偏差型知识的内容。
Data Mining mainly studies on research Generalization Knowledge, Association Knowledge, Classification Knowledge, Clustering Knowledge, Prediction Knowledge, and Deviation Knowledge.
数据挖掘主要研究内容包括广义知识、关联知识、分类知识、聚类知识、预测型知识和偏差型知识的内容。
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