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Description: 利用谱聚类方法在特
征向量空间中对原始样本数据进行重新表述使得在新表述中同一聚类中的样本能够更好地积聚在一起构建聚类核函数 并进而构造聚类核半监督支持向量机 使样本更好地满足半监督学习必须遵循的聚类假设 -Restated in the new formulation in the same cluster sample be better able to accumulate together to build the clustering of nuclear function and thus to construct the semi-supervised clustering of nuclear support vector method of spectral clustering in the feature vector space of the original sample data machine so that the sample to better meet the needs of semi-supervised learning clustering assumptions that must be followed
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Size: 155648 |
Author: 小白 |
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Description: Support Vector Machine (and Statistical Learning Theory) Tutorial by Jason Weston
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Size: 701440 |
Author: akbar partovi |
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Description: An introduction to Support Vector Machine implementations in MATLAB (MATLAB Workshop)
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Size: 153600 |
Author: akbar partovi |
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Description: svm(support vector machin) code usefull for classification-svm(support vector machin) code usefull for classification
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Size: 63488 |
Author: parham |
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Description: 改进的P_SVM支持向量机与遥感数据分类,对多光谱高光谱分类-Improved P_SVM support vector machines and remote sensing data classification, Classification of multispectral hyperspectral
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Size: 1503232 |
Author: ww1 |
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Description: 支持向量机模型研究及应用，本文所做的工作主要在如下几个方面：
1)运用模糊集理论(FST)和概率理论对支持向量机进行研究，构造出了概率模糊支
持向量机(PFSVM)模型，既达到了减少或者消除外围异样点对于整个训练模型的影响，-Support vector machine model and application, this work mainly in the following aspects: 1) the use of fuzzy set theory (FST) and the probability theory of support vector machines, constructed out of the probabilistic fuzzy support vector machine (PFSVM) model, not only to reduce or eliminate abnormal points outside the training model for the effects of
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Size: 2335744 |
Author: ww1 |
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Description: 提出了一种支持矢量机的汉语声调识别新方法。论文首先在基频和对数能量的基础上，建立了一个适合于支
持矢量机分类的等维声调特征。然后对支持矢量机的多分类策略和不同核函数对声调识别的影响进行了实验研究。
与BP神经网络相比，支持矢量机具有更高的识别率和更强的推广能力。-This paper presents a novel support vector machine based Chinese tone recognition method．A
new tone recognition feature is first ex血acted using the fundamental frequency(FO)and logarithmic
energy．And how to select the method of SVM multi-class classification and kernel function is also discussed
by experiments．Compared with BP neural network，SVM has higher recognition rates and more strong
generalization．
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Size: 472064 |
Author: 沈 |
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Description: Support vector based fuzzy for pattern classification
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Size: 486400 |
Author: sengottaiyan |
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Description: 基于模糊神经的支持向量机非线性系统控制，利用模糊神经SVM对非线性系统进行控制-Support vector machines based neuro-fuzzy control of nonlinear systems
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Size: 735232 |
Author: lichi |
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Description: 通过训练的支持向量机具有特定目标边缘识别能
力，克服了传统边缘检测算法无目标性，噪音大的缺点。
-Ability to identify specific target edge training support vector machine, to overcome the traditional edge detection algorithm targeted noise shortcomings.
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Size: 3987456 |
Author: 韩子晨 |
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Description: this code is about Support Vector Regression.
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Size: 2048 |
Author: hamed |
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Description: 超球体支持向量机是单类支持向量机的一种，超球体OC-SVM算法的思想为寻找一个超球体，使其半径尽可能小的同时，包含的训练样本数尽可能多。-Hypersphere support vector machine is a single-class support vector machine, thought hypersphere OC-SVM algorithm to find a hypersphere, so radius as small as possible while the number of training samples contain as much as possible.
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Size: 18432 |
Author: 王超 |
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Description: Support Vector Machines
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Size: 560128 |
Author: mahran omairy |
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Description: A Tutorial on Support Vector Machines for Pattern Recognition - Burges - 1997
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Size: 615424 |
Author: sam |
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Description: Least squares support vector machine SVM toolbox self code and installation methods, useful, tried
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Size: 36864 |
Author: DY |
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Description: 用最小二乘支持向量机的算法做一个对正弦波信号的跟踪，跟踪效果很好-Using least squares support vector machine algorithm to make one pair of sine wave signal tracking, tracking works well
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Size: 22528 |
Author: 望初 |
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Description: Location prediction is a special case of spatial data mining
classification. For instance, in the public safety domain,
it may be interesting to predict location(s) of crime
hot spots. In this study, we present Support Vector Machine
(SVM) based approach to predict the location as alternative
to existing modeling approaches. SVM forms the new generation
of machine learning techniques used to find optimal
separability between classes within datasets. Experiments
on two different spatial datasets show that SVMs gives reasonable
results.
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Size: 197632 |
Author: ahmed |
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Description: Crime hot-spot location prediction is important for public safety. The output from the prediction
can provide useful information to improve the activities aimed at detecting and preventing
safety and security problems. Location prediction is a special case of spatial data mining classification.
For instance, in the public safety domain, it may be interesting to predict location(s) of
crime hot spots. In this study, we present a support vector machine (SVM)-based approach to predict
the location as an alternative to existing modeling approaches.
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Size: 453632 |
Author: ahmed |
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Description: 这是一本机器学习和数据挖掘方向的书籍，对学习支持向量机有很好的帮助。-This is a direction of machine learning and data mining books, learning support vector machine has a good help.
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Size: 7763968 |
Author: zzl |
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Description: 用支持向量机svm实现分类与函数回归，其中包括svc程序，svc输出程序以及svr绘图程序-Classification and function regression using support vector machine svm, including svc program, svc output of the program as well as a drawing program svr
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Size: 79872 |
Author: gongwenwen |
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