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Description: This is SvmFu, a package for training and testing support vector
machines (SVMs). It s written in C++. It uses templates. The
advantage of templates is that the types of kernel values and data
points can be varied to suit the problem.-This is SvmFu, a package for training and testing support vector
machines (SVMs). It s written in C. It uses templates. The advantage
of templates is that the types of kernel values and data points can be
varied to suit the problem.
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Size: 112344 |
Author: 刘霞 |
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Description: 有向无环图支持向量(DAG-SVMS)多类分类方法,是一种新的多类分类方法。该方法采用了最小超球体类包含作为层次分类依据。试验结果表明,采用该方法进行多类分类,跟已有的分类方法相比有更高的分类精度。
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Size: 5049 |
Author: 苏苏 |
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Description: New training algorithm for linear classification SVMs that can be much faster than SVMlight for large datasets. It also lets you direcly optimize multivariate performance measures like F1-Score, ROC-Area, and the Precision/Recall Break-Even Point.
Platform: |
Size: 87142 |
Author: 张山 |
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Description: MSJ-06Ⅱ-A 美国UNION UNION FLAG 型式番号:SVMS-01 欧洲联盟AEU AEU ENACT 型式番号:AEU-09 AEU ENACT(量产型) 型式编号:AEU-09
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Size: 260881 |
Author: zlh |
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Description: New in this version:
Support for multi-class pattern recognition using maxwins, pairwise [4] and DAG-SVM [5] algorithms.
A model selection criterion (the xi-alpha bound [6,7] on the leave-one-out cross-validation error).
-New in this version : Support for multi-class pattern recognition u maxwins sing, Pairwise [4] and DAG- SVM [5] algorithms. A mode l selection criterion (the xi-alpha bound [6, 7] on the leave-one-out cross-validation erro r).
Platform: |
Size: 43008 |
Author: 吴成 |
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Description: This is SvmFu, a package for training and testing support vector
machines (SVMs). It s written in C++. It uses templates. The
advantage of templates is that the types of kernel values and data
points can be varied to suit the problem.-This is SvmFu, a package for training and testing support vector
machines (SVMs). It s written in C. It uses templates. The advantage
of templates is that the types of kernel values and data points can be
varied to suit the problem.
Platform: |
Size: 111616 |
Author: 刘霞 |
Hits:
Description: 有向无环图支持向量(DAG-SVMS)多类分类方法,是一种新的多类分类方法。该方法采用了最小超球体类包含作为层次分类依据。试验结果表明,采用该方法进行多类分类,跟已有的分类方法相比有更高的分类精度。
-Directed acyclic graph support vector (DAG-SVMS) multi-category classification methods, is a new multi-category classification methods. The method uses the smallest category of super-sphere that contains the level of classification as a basis. The experimental results show that using the method of multiclass classification with the classification method has been compared to a higher classification accuracy.
Platform: |
Size: 5120 |
Author: 苏苏 |
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Description: New training algorithm for linear classification SVMs that can be much faster than SVMlight for large datasets. It also lets you direcly optimize multivariate performance measures like F1-Score, ROC-Area, and the Precision/Recall Break-Even Point.
Platform: |
Size: 87040 |
Author: 张山 |
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Description: MSJ-06Ⅱ-A 美国UNION UNION FLAG 型式番号:SVMS-01 欧洲联盟AEU AEU ENACT 型式番号:AEU-09 AEU ENACT(量产型) 型式编号:AEU-09
-MSJ-06 Ⅱ-A USA UNION UNION FLAG type designation: SVMS-01 European Union AEU AEU ENACT type designation: AEU-09 AEU ENACT (production type) type ID: AEU-09
Platform: |
Size: 260096 |
Author: zlh |
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Description: This example demonstrates how to use WEKA s SVMs classifier in Matlab.
Platform: |
Size: 50176 |
Author: huglepzh |
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Description: 支持向量机几个算法源代码
包括以下算法
cSVM3.1.8
libsvm-2.88
newsvm
OnlineSVR_C--_Code
svmcla-cSVM3.1.8
libsvm-2.88
newsvm
OnlineSVR_C--_Code
svmclass
Platform: |
Size: 4442112 |
Author: zidianwjq |
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Description: 支持向量机核函数方面的近期外文参考[08-09]-some references about SVMs
Platform: |
Size: 6737920 |
Author: zidianwjq |
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Description: 支持向量机核函数方面的近期外文参考[08-09]-Support Vector Machine Kernel its recent foreign-language reference [08-09]
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Size: 9998336 |
Author: zidianwjq |
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Description: 这是一个100 %纯Java库,您可以使用适用于N元
分析技术的过程分为文本文件。
该计划包括几个不同的分类算法, namelly
支持向量机,贝叶斯Logistic回归,神经网络分类和文本压缩 算法。如支持向量机和贝叶斯Logistic回归,一个 “一对一” 用于多类分类。更详细的说明这些学习算法和可用的选项,请提供的javadocs 。-It is a 100 pure Java library that you can use to apply N-Gram
analysis techniques to the process of categorizing text files.
The package includes several different categorization algorithms, namelly
SVMs, Bayesian Logistic Regression, NN classification and a text compression
based algorithm. In the case of SVM and Bayesian Logistic Regression, a
"one-against-one" apprach is used for multiclass classification. For a more detailed description of these learning algorithms and the available options please consult the supplied javadocs.
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Size: 838656 |
Author: liwen |
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Description: Paper implementation of
A Modifi ed Finite Newton Method for Fast Solution of Large Scale
Linear SVMs
S. Sathiya Keerthi and Dennis DeCoste
Published in Journal of Machine Learning Research - March,2005-Paper implementation of
A Modifi ed Finite Newton Method for Fast Solution of Large Scale
Linear SVMs
S. Sathiya Keerthi and Dennis DeCoste
Published in Journal of Machine Learning Research- March,2005
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Size: 5120 |
Author: Chetan J |
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Description: 图像标注中的 基于SVM的图像目标检测算法-image annotation, SVMs for Object Detection and Beyond
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Size: 1520640 |
Author: 午阳 |
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Description: Handwriting (SVMs) Programs-Handwriting (SVMs)
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Size: 243712 |
Author: 宗晓 |
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Description: Gestures (SVMs) Machine Learning-Gestures (SVMs)
Platform: |
Size: 44032 |
Author: 宗晓 |
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Description: Machine Learning Regression (SVMs)
Platform: |
Size: 43008 |
Author: 宗晓 |
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Description: Machine Learning Feature Selection (SVMs)
Platform: |
Size: 76800 |
Author: 宗晓 |
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