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Libsvm is a simple, easy-to-use, and efficient software for SVM
classification and regression. It can solve C-SVM classification,
nu-SVM classification, one-class-SVM, epsilon-SVM regression, and
nu-SVM regression. It also provides an automatic
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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
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Libsvm is a simple, easy-to-use, and efficient software for SVM
classification and regression. It solves C-SVM classification, nu-SVM
classification, one-class-SVM, epsilon-SVM regression, and nu-SVM
regression. It also provides an automatic mo
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libsvm is a simple, easy-to-use, and efficient software for SVM
classification and regression. It solves C-SVM classification, nu-SVM
classification, one-class-SVM, epsilon-SVM regression, and nu-SVM
regression. It also provides an automatic mo
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最新的支持向量机工具箱，有了它会很方便 1. Find time to write a proper list of things to do! 2. Documentation. 3. Support Vector Regression. 4. Automated model selection. REFERENCES ========== [1] V.N. Vapnik, \"The Nature of Statistical Learning Theory\", Springer-Verl
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支持向量机的代码库，使用简单，主要用途是基于支持向量机的分类和回归。还包括C-SVM，nu-SVM，一类SVM，epsilon回归等功能。它还提供了用于C-SVM的自动模型选择工具。-Libsvm is a simple, easy-to-use, and efficient software for SVM
classification and regression. It solves C-SVM classification, nu-SVM
classification, one-
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0下载：
Libsvm is a simple, easy-to-use, and efficient software for SVM
classification and regression. It solves C-SVM classification, nu-SVM
classification, one-class-SVM, epsilon-SVM regression, and nu-SVM
regression. It also provides an automatic mo
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支撑向量机SVM的工具LIBSVM，能够在windows平台下通过命令行使用，也可以在matlab下调用，适合于研究复杂条件下的分类问题-Libsvm is a simple, easy-to-use, and efficient software for SVM
classification and regression. It solves C-SVM classification, nu-SVM
classification, one-class-SVM, epsilon-SVM
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0下载：
Libsvm is a simple, easy-to-use, and efficient software for SVM
classification and regression. It solves C-SVM classification, nu-SVM
classification, one-class-SVM, epsilon-SVM regression, and nu-SVM
regression. It also provides an automatic mo
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library for SVMclassification and regression. It solves C-SVM classification, nu-SVM
classification, one-class-SVM, epsilon-SVM regression, and nu-SVM
regression. It also provides an automatic model selection tool for
C-SVM classification.
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是一種線性方成的分類器。SVM透過統計的方式將雜亂的資料以NN的方式分成兩類，以便處理。LIBLINEAR is a linear classifier for data with millions of instances and features. It supports L2-regularized logistic regression (LR), L2-loss linear SVM, and L1-loss linear SVM. -Main features of LIBLINEA
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svm model selection by pso
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A distributed PSOSVM hybrid system with feature selection and parameter optimization
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This study proposed a novel PSO–SVM model that hybridized the particle swarm optimization (PSO) and support vector machines (SVM) to
improve the clas
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台湾林智仁编写的支持向量机开源程序，可用于分类（C-SVC，nu-SVC，one-class SVM）和回归（epsilon-SVR，nu-SVR）。这是最新版本3.0。-Libsvm3.0 is a simple, easy-to-use, and efficient software for SVM
classification and regression. It solves C-SVM classification, nu-SVM
classification, one-cla
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针对基于GPS／GIS的浮动车数据特点，总结其中无效的数据类型，并给出数据有效处理的方法。以支持向量机原理、交通状态预测方法为基础，分析了常用支持向量回归机、核函数及模型参数的性能，以及各核函数及模型参数对支持向量机性能的影响及作用。针对路段平均速度预测中的小样本、非线性、高维回归等特点，将支持向量回归机方法引入基于浮动车数据的路段车辆速度预测，构建了路段平均速度短时预测模型。并以杭州市某路段的实际数据为例，详细阐述了支持向量回归机预测模型的具体建模和求解过程。运用LibSVM2．84软件包，进
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机器学习matlab源代码，包括多分类SVM，模式识别，特征选择，回归等算法。-The spider is intended to be a complete object orientated environment for machine learning in Matlab. Aside from easy use of base learning algorithms, algorithms can be plugged together and can be compared with
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matlab源文件，对网络数据进行入侵检测，利用libsvm工具箱，对特征进行分类。内容包括：数据的归一化，参数择优（交叉验证），建立svm模型，性能评价。压缩包内有详细的说明文档。-matlab source files, network data for intrusion detection, to use libsvm toolbox, to classify the characteristics. The contents include: data normalization, p
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LS-SVM Leave-One-Out Cross-Validation Demo
G. C. Cawley, "Leave-one-out cross-validation based model selection criteria for weighted LS-SVMs", Proceedings of the International Joint Conference on Neural Networks (IJCNN-2006), pages 1661-1668, Vanco
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支持向量机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有线性回归和非线性回归,其模型的选 择包括核的选择、容量控制以及损失函数的选择.在控制方面的研究包括非线性 时间序列 的预测及应用、系统辨识以及优化控制和学习控制等方面的研究-Support vector machine (SVM) regression theory and neural network has many unique advantages such as nonlinear regression theory
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window下的文本分类工具tmSVM，该系统在封装 libsvm 、 liblinear 的基础上，又增加了 特征选择 、 LSA特征抽取 、 SVM模型参数选择 、 libsvm格式转化模块 以及一些实用的工具。-Text categorization tool tmSVM under the window, the system on the basis of encapsulation libsvm, liblinear, added feature selection, LSA fea
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