| 释义 |
standard SVM
基本例句
标准支持向量机
Compared with thestandard SVMalgorithm, the experiments show our new classifier can both improve the classification accuracy and reduce the bias.实验表明，新的基于SVM的分类器与传统SVM相比较，在分类准确率上有很大提高，同时偏差有所降低。
It is different form the standard Support vector machine : The margin is measured by fixed norm and the optimization problems depend on the parameters in thestandard SVM.它和标准的支持向量机不同：标准的支持向量机采用固定的模度量间隔且最优化问题与参数有关。
Combining this idea withstandard SVMclassifier and adding a mixed data sets near the interface, a new SVM learning algorithm is proposed for classification of small data sets.在标准SVM分类器训练方法中融入这种思想，给分类面附近加入混合数据，提出了一种新的基于SVM的分类器设计方法，并将这种方法应用于小样本数据的分类问题中。
Based on standard support vector machines , the algorithm of cost-sensitive SVM is proposed by integrating misclassification cost of each sample intostandard SVM.针对此缺隙，并基于标准的SVM，通过在SVM的设计中集成样本的不同误分类代价，提出代价敏感支持向量机的设计方法。
Experiments show that the ensemble system combines the advantages of the two subsystems, and outperforms each of the subsystems and thestandard SVMsystem.数值实验表明：集成分类系统通过自适应训练权重，综合了两种特征提取子分类器的优点，具有更好的综合性能。
To the problem that thestandard SVMdoes not provide probabilities output, the probabilistic outputs for support vector machines is modeled based on the maximum entropy estimation.针对传统的支持向量机方法不能提供后验概率的输出问题，从信息熵的角度采用最大熵估计方法，直接对支持向量机输出进行后验概率建模。 |