It is a very challenging work to deal with large regression problems based on support vector machines.
基于支持向量机的大样本回归问题一直是一个非常具有挑战性的课题。
Support vector machines (SVM) are a kind of novel machine learning methods, based on statistical learning theory, which have been developed for solving classification and regression problems.
支持向量机是一种基于统计学习理论的新颖的机器学习方法，该方法已广泛用于解决分类和回归问题。
Least square support vector machines regression without sparsity needs longer training time currently, and is not adapted to online real-time training.
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。
Support vector machines (SVM) are a kind of novel machine learning methods based on statistical learning theory, which has been developed to solve classification and regression problems.
支持向量机是一种基于统计学习理论的新颖的机器学习方法，该方法已广泛用于解决分类和回归问题。
For linear support vector ordinal regression machines, some theoretical aspects are studied in this paper.
本文主要对线性支持向量顺序回归机进行理论研究。
As new technology of data mining, support vector machines (SVM) have been successfully applied in pattern recognition and regression problem, et al.
支持向量机作为数据挖掘的一项新技术，应用于模式识别和处理回归问题等诸多领域。
In the stage I, called as data preprocessing, the support vector machines for regression (SVMR) approach is used to filter out the outliers in the training data set.
第一阶段称为所谓的资料预先处理，即使用支援向量回归来找出训练资料集中的离异点并删除之。
Kernal methods and support Vector Machines (SVMs) are related to Gaussian processes and can also be used in classification and regression problems.
内核方法和支持向量机(SVMs)与高斯过程相关并应用于分类和回归问题。
A novel adaptive support vector regression neural network (SVR-NN) is proposed, which combines respectively merits of support vector machines and a neural network.
一种新的自适应支持向量回归神经网络(SVR - NN)提出，它结合了分别支持向量机和神经网络的优点。
The support vector machines theory is shown to have excellent performance compared with other non-linear regression, such as neural networks.
支持向量机（SVM）回归理论与神经网络等非线性回归理论相比具有许多独特的优点。
The support vector machines theory is shown to have excellent performance compared with other non-linear regression, such as neural networks.
支持向量机（SVM）回归理论与神经网络等非线性回归理论相比具有许多独特的优点。
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