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1)  Fuzzy support vector classifier (F_SVC)
模糊支持向量分类器(F_SVC)
2)  fuzzy support vector classification
模糊支持向量机分类
3)  Fuzzy Support Vector Classifiers
模糊支持向量分类机
1.
Fuzzy Support Vector Classifiers as a new means, by combining the fuzzy theories and Support Vector Classifiers together, is proposed to solve the problem that SVC is sensitive to noises or outliers in the training set.
模糊支持向量分类机是将模糊集合理论与支持向量分类机相结合,针对支持向量分类机对训练样本集合中噪声点或孤立点的敏感性问题而提出的一种新方法。
4)  support vector classifier
支持向量分类器
1.
To solve the problem of the low sampling efficiency in the contentbased information retrieval, a new classifier named 15-class support vector classifier (15 SVC) is proposed.
针对基于内容的信息检索中负样本抽样效率低的问题,设计了1 5类支持向量分类器。
2.
To improve the speed and the problem of high false positive in micro-calcification detection,a novel micro-calcification detection method based on support vector classifier model with rejection feature and Iterative Rank-order Filter Subspace is proposed.
对于输入模式,首先利用基于最大软间隔超平面的支持向量分类器(SVC)进行分类判决;然后对真实的钙化点样本特征空间求取最小的包含球形边界,得到钙化点样本的球形支持向量域表示(SVDD)。
5)  support vector classifier(SVC)
支持向量分类器
1.
Firstly the first layer of support vector classifier(SVC) with maximum margin between two classes will be used for classifying the input pattern;then the sphere support vectors of true micro-calcification points to describe the distribution of the sample were obtained by searching all the sphere boundaries containing the samples of this class.
检测时,首先利用基于最大间隔超平面的支持向量分类器(SVC)对输入模式进行分类判决;然后通过求取真实钙化点样本特征空间最小的包含球形边界来得到钙化点样本的球形支持向量域表示(SVDD);接着利用钙化点的支持向量域表示对输入模式进行拒识或接受处理;最后利用SVC与SVDD两个分类器的结果来进行综合判决。
6)  fuzzy one-class support vector machine
模糊一类支持向量机
补充资料:50t炼钢电弧炉电抗器、电阻器(SVC)(大冶钢厂)


50t炼钢电弧炉电抗器、电阻器(SVC)(大冶钢厂)


50t炼钢电弧炉电抗器、电阻器(SVC)(大冶钢厂)
说明:补充资料仅用于学习参考,请勿用于其它任何用途。
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