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The hyperplane revises the error of the standard Support Vector Machines. 该分类面校正了标准的支持向量机的分类误差。
Karhunen-Loeve transform is employed to get the representation basis of face image set, then use support vector machines to recognize. 摘要利用K-L变换首先对人脸图像进行特征参数提取，再利用支持向量机进行识别。
A new geometric fast incremental learning algorithm for support vector machines (SVM) was proposed. 摘要提出了一种新的基于壳向量的增量式支持向量机快速学习算法。
The separating hyperplane of traditional support vector machines is sensitive to noises and outliers. 摘要传统的支持向量机分类超平面对噪声和野值非常敏感。
A method is proposed to construct sparse least squares support vector machines (LSSVMs). 摘要提出一种构造稀疏化最小二乘支持向量机的方法。
Then, the classifier with multi-class support vector machines of DDAG (decision directed acyclic graph) is given. 然后，用有向无环图的多类支持向量机进行分类。
A nonlinear predictive control algorithm based on least squares support vector machines (LS-SVM) model was proposed. 提出一种基于最小二乘支持向量机(LS-SVM)的非线性系统预测控制算法。
It might be a very fancy calculator such as R, Matlab, Mathematica, or a even C library for support vector machines. ”嗨;”你会思索;”我了解这个.;这是乘法符号!”
The PCG analysis algorithm based on support vector machines successfully identify nine types of heart disease. 以支持向量机为基础之心音图辨认演算法可以成功的将九种心音辨认出来。
The Support Vector Machines(SVM) based on ethe Statistical Learning Theory can solve this problem. 而基于统计学习理论的支持向量机(SVM) 方法正好克服了这方面的不足。
A texture classification algorithm based on Dual-tree Complex Wavelet Transform (DT-CWT) and Support Vector Machines (SVM) is proposed. 提出了一种基于双树复数小波变换(DT-CWT)和支持向量机(SVM)的纹理分类算法。
In this class we describe Support Vector Machines for regression estimation and illustrate the connection between SVMs and Basis Pursuit De-Noising. 课中将叙述支持向量机的回归估算法并举例说明支持向量机和基础追踪去杂讯法之间的关系。
When traditional support vector machines separate data containing noises, the obtained hyperplane is not an optimal one. 使用传统的支持向量机对含有噪声的数据分类时，所得到的超平面往往不是最优超平面。
Least square support vector machines regression without sparsity needs longer training time currently, and is not adapted to online real-time training. 摘要现有最小二乘支持向量机回归的训练和模型输出的计算需要较长的时间，不适合在线实时训练。
BVM(Ball Vector Machine)is a faster machine learning algorithm than SVM. 球向量机是一种比SVM更快的机器学习方法。
Wavelet and support vector machine are used to classify the audio clips. 使用小波变换和支持向量机的方法对音频进行分类。
In this paper, an intelligent method for solving multiple attribute decision making(MADM) problems is proposed based on support vector machines(SVM). 摘要分析多属性决策问题及现有方法，提出了基于支持向量机的智能多属性决策方法。
Fortunately, Statistical learning theory (SLT) and support vector machines (SVM) provide methods to solve the problems mentioned above. 与传统统计学方法相比，统计学习理论是一种专门研究小样本情况下机器学习规律的理论。
Rule-Based Reasoning (RBR), Case-Based Reasoning (CBR) and Support Vector Machines (SVM) were integrated to support the diagnosis management. 应用集成规则推理、案例推理和支持向量机，共同应对供应链伙伴关系诊断管理问题。
Support vector machines(SVM),a learning method based on statistical learning theory(SLT),can solve small sample learning problems better. 支持向量机是建立在统计学习理论上的一种学习算法，较好地解决了小样本学习问题。