Model selection is an important research direction in SVM.
模型选择是支持向量机一个重要的研究方向。
Support vector machine (SVM) is a new machine learning technique.
支持向量机(SVM)是一种新型的机器学习方法。
Then, we implement classification modeling and forecast based on SVM.
然后基于支持向量机进行分类建模和预测过程。
This is the paper in which the relation between SVM and BPD is studied.
文章中讨论支持向量机与基础追踪去杂讯法之间的关系。
When this is complete, identify slices that are available for use by the SVM.
完成此工作以后，标识可供SVM使用的片。
The torque ripple could be significantly reduced by SVM-based DTC scheme.
基于SVM的DTC方案可以有效地减小转矩波动。
This file specifies whether the VMX (Intel) or SVM (AMD) extensions are supported.
这个文件指定了是否支持vmx (Intel)或svm (amd)扩展。
SVM for text classification - tutorial on machine learning? How do I get started?
SVM文本分类的机器学习教程？我如何开始？
The SVM saves all information about structures of volumes on a disk area called the replica.
SVM将有关卷结构的所有信息都保存在一个称为副本(replica)的磁盘区中。
However, boosting- or SVM-based methods will require more training images to get good results.
然而，用增强型的或者基于SVM方法要得出好的结果需要更多的图片。
The prediction method of network delays based on support vector machine (SVM) was put forward.
进而提出了基于支持向量机(SVM)的网络延时预测方法。
In this thesis, SVM as a new machine learning method is brought into medical image classification.
论文将支持向量机的机器学习方法引入到医学图像的分类问题。
It also discusses the primary processing and recognition diagram of SVM applied to face recognition.
还讨论支持向量机用于人脸识别的主要处理流程和识别框图。
The support vector machine(SVM) is a new learning technique based on the statistical learning theory.
支持向量机（SVM）是根据统计理论提出的一种新的学习算法。
SVM provides you with the ability to manage large number of disks, and it also improves data availability.
SVM为您提供管理大量磁盘的能力，同时可以改进数据的可用性。
In the SVM-based speaker recognition system study, it is important to obtain a ideal recognition rate.
在基于SVM的说话人识别系统研究中，如何获得理想的识别率是亟待解决的问题。
To mirror and use LVM without VERITAS, you would have to bring these filesystems under the control of SVM.
要在不使用VERITAS的情况下镜像和使用LVM，就必须让这些文件系统受s VM控制。
To check for compatibility, run the command grep vmx /proc/cpuinfo (on AMD, run the command grep svm /proc/cpuinfo).
为了检查兼容性，请运行命令grepvmx /proc/cpuinfo（对于 AMD，运行命令 grep svm /proc/cpuinfo）。
The SVM state database stores configuration and states information about volumes, including hot spares and disk sets.
SVM状态数据库存储有关卷的配置和状态信息，包括热备份磁盘 (hot spares) 和磁盘集。
This paper presents a Support Vector Machine (SVM) method for classification of dynamic power quality disturbances.
论文将支持向量机引入到动态电能质量分类问题中。
Support vector machine (SVM) is a new generation machine learning technique based on the statistical learning theory.
支持向量机(SVM)是基于统计学习理论的新一代机器学习技术。
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。
SVM based inverse model of nonlinear system is used as feed-forward controller to form direct inverse model controller.
由SVM辨识的逆模型作为前馈控制器，形成直接逆模型控制器。
A new prediction approach for railway passenger volume is put forward by means of Least Squares Support Vector Machine (LS-SVM).
提出了一种基于最小二乘支持向量机(LS - SVM)的铁路客运量预测的新方法。
A novel prediction model for remaining capacity of batteries based on least square support vector machine (LS-SVM) was proposed.
提出了一种最小二乘支持向量机的电池剩余电量预测新模型。
This paper mainly focuses on the prediction problem by the application of hybrid and ensemble thinking into the modeling base on SVM.
本文基于混合学习和集成学习的思想，将这两种方法应用于支持向量机建模技术中，主要解决预测分析问题。
Kernel function is the key technology of SVM, the choice of kernel will affect the learning ability and generalization ability of SVM.
核函数是SVM的关键技术，核函数的选择将影响着支持向量机的学习能力和泛化能力。
Recent enhancements to SVM include support for multiterabyte volumes, cluster volume manager, and thousands of partitions per physical disk.
最近对SVM进行的增强包括支持multiterabyte卷和ClusterVolumeManager，以及支持在每个物理磁盘上划分数千个分区。
The learning discipline of SVM is to minimize the structural risk instead of empirical risk, hence the better extensibility is guaranteed.
同时，由于该方法建立在结构风险最小化准则上，而不是仅仅使经验风险最小，所以，它具有好的推广能力。
A new SVM iterative algorithm is proposed, aiming at the problem that the speeds of learning and classifying are slow in large training set.
针对SVM方法在大样本情况下学习和分类速度慢的问题，提出了大样本情况下的一种新的SVM迭代训练算法。
应用推荐