• 第4支持向量部分进展

    Chapter 4, The Some Development of Support Vector Machine.

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  • 支持向量一种新的学习方法

    Support Vector machine is a new method of machine learning.

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  • 支持向量一种新的学习方法

    Support vector machine is a new kind of machine learning method.

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  • 模型选择支持向量机一个重要研究方向

    Model selection is an important research direction in SVM.

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  • 提出一种基于支持向量改进方法

    In this paper we present an improved dimensionality reduction method based on support vector machines.

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  • 然后基于支持向量机进行分类建模预测过程。

    Then, we implement classification modeling and forecast based on SVM.

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  • 论文支持向量引入动态电能质量分类问题中。

    This paper presents a Support Vector Machine (SVM) method for classification of dynamic power quality disturbances.

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  • 提出伺服系统支持向量辨识建模方法

    A method of the electro hydraulic servo system identification modeling is presented based on support vector machines.

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  • 支持向量(SVM)一种新型学习方法

    Support vector machine (SVM) is a new machine learning technique.

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  • 本文提出对手写相似汉字进行识别支持向量方法

    This paper presents a recognition method of similar Chinese handwriting by support vector machine.

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  • 文章讨论支持向量基础追踪去杂讯法之间关系

    This is the paper in which the relation between SVM and BPD is studied.

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  • 本文首次采用支持向量方法医学图像进行了分类研究

    This paper firstly investigates the application of support vector machines for medical image classification.

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  • 进而提出基于支持向量(SVM)网络延时预测方法

    The prediction method of network delays based on support vector machine (SVM) was put forward.

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  • 提出一种最小二乘支持向量电池剩余电量预测模型

    A novel prediction model for remaining capacity of batteries based on least square support vector machine (LS-SVM) was proposed.

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  • 讨论支持向量机用于人脸识别主要处理流程识别框图

    It also discusses the primary processing and recognition diagram of SVM applied to face recognition.

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  • 论文支持向量机学习方法引入医学图像分类问题

    In this thesis, SVM as a new machine learning method is brought into medical image classification.

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  • 支持向量SVM根据统计理论提出一种新的学习算法

    The support vector machine(SVM) is a new learning technique based on the statistical learning theory.

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  • 提出基于支持向量分类原理鸢尾属植物进行分类方法

    This article presents a new method of plant classification of iris based on the support vector machine classification principle.

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  • 实验结果表明采用支持向量方法进行变异语音分类可行的。

    Experimental results indicate that it is feasible to adopt SVMs for stressed speech classification.

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  • 支持向量(SVM)基于统计学习理论一代学习技术

    Support vector machine (SVM) is a new generation machine learning technique based on the statistical learning theory.

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  • 这种学习可以使用神经网络或者支持向量不过决策可以实现类似的功能。

    This sort of learning could take place with neural networks or support vector machines, but another approach is to use decision trees.

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  • 最后一个主题将讲解支持向量分类物核心使用的可训练物件侦测系统

    The last topic is about a trainable object detection system using at its core a Support Vector Machine classifier.

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  • 支持向量用作说话确认模型训练目标说话人和背景说话人语音数据。

    The support vector machine based speaker verification models are trained on the enrolled speaker and the background model.

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  • 介绍了一种基于支持向量混合气体红外光谱组分浓度和种类分析方法

    A new method of infrared spectrum analysis based on support vector machine for mixture gas was proposed.

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  • 支持向量支持向量相关VC怎样一个公式关于两个

    How is the VC dimension of a support-vector machine related to its number of support vectors? Is there a formula relating these two quantities?

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  • 提出支持向量-模糊预测控制方法,介绍支持向量机列车启动控制过程中的应用

    It is proposed a fuzzy forecast control method based on support vector machine. The applications of the machine to the train start-up control are given.

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  • 目前支持向量模式识别函数逼近数据挖掘文本自动分类中均好的应用

    Recently, Support Vector Machine is well applied in pattern recognition, function approximate, data mining and text auto categorization.

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  • 提出种基于最小二乘支持向量(LS - SVM)铁路客运量预测方法

    A new prediction approach for railway passenger volume is put forward by means of Least Squares Support Vector Machine (LS-SVM).

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  • 大部分数字识别工作可以由神经网络来完成最近支持向量被证明可以分类方面做得更好

    Much of the work on digit recognition has been done in the neural network community, but more recently support vector machines have proven to be even better classifiers.

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  • 大部分数字识别工作可以由神经网络来完成最近支持向量被证明可以分类方面做得更好

    Much of the work on digit recognition has been done in the neural network community, but more recently support vector machines have proven to be even better classifiers.

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