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: 基于核分析的多类分类器，支持向量机的多类分类，适合研究学习，欢迎同行下载-Kernel-based analysis of the many types of classifier, support vector machine multi-category classification, suitable for study of learning, welcomed the peer download Platform: |
Size: 417792 |
Author:lwen |
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Description: svm(支持向量机)分类算法本质上是二类分类器，实现多类分类的方法一般是将多类分类看作是多个一对多的二类分类器。本程序就是基于svmlight的svm多类分类器实现。对分类感兴趣的用户请参照。配合中文分词（参见我上传的程序），可实现中文多类分本分类。-svm (support vector machine) classification algorithm is essentially a second-class classifier, multi-category classification methods in general is to multiclass classification is more than one-to-many as second-class classifier. This procedure is based on many types of svmlight of SVM classifiers to achieve. Classification please refer to interested users. With the Chinese word segmentation (see my uploaded program), can be realized at the Chinese multi-category classification. Platform: |
Size: 566272 |
Author:maming |
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Description: 统计模式识别工具箱（Statistical Pattern Recognition Toolbox）包含：
1，Analysis of linear discriminant function
2，Feature extraction: Linear Discriminant Analysis
3，Probability distribution estimation and clustering
4，Support Vector and other Kernel Machines-
This section should give the reader a quick overview of the methods implemented in
STPRtool.
• Analysis of linear discriminant function: Perceptron algorithm and multiclass
modification. Kozinec’s algorithm. Fisher Linear Discriminant. A collection
of known algorithms solving the Generalized Anderson’s Task.
• Feature extraction: Linear Discriminant Analysis. Principal Component Analysis
(PCA). Kernel PCA. Greedy Kernel PCA. Generalized Discriminant Analysis.
• Probability distribution estimation and clustering: Gaussian Mixture
Models. Expectation-Maximization algorithm. Minimax probability estimation.
K-means clustering.
• Support Vector and other Kernel Machines: Sequential Minimal Optimizer
(SMO). Matlab Optimization toolbox based algorithms. Interface to the
SVMlight software. Decomposition approaches to train the Multi-class SVM classifiers.
Multi-class BSVM formulation trained by Kozinec’s algorithm, Mitchell-
Demyanov-Molozenov algorithm Platform: |
Size: 4271104 |
Author:查日东 |
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Description: 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 LIBLINEAR include
Same data format as LIBSVM, our general-purpose SVM solver, and also similar usage
Multi-class classification: 1) one-vs-the rest, 2) Crammer & Singer
Cross validation for model selection
Probability estimates (logistic regression only)
Weights for unbalanced data
MATLAB/Octave, Java interfaces
Platform: |
Size: 521216 |
Author:陳彥霖 |
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Description: svm多分类器，包括多分类和GA算法和PSO算法优化的SVM-svm multi-classifier, including the multi-classification and GA algorithm and PSO algorithm for optimization of SVM Platform: |
Size: 494592 |
Author:何同学 |
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Description: In this paper, we show how support vector machine (SVM) can be
employed as a powerful tool for $k$-nearest neighbor (kNN)
classifier. A novel multi-class dimensionality reduction approach,
Discriminant Analysis via Support Vectors (SVDA), is introduced by
using the SVM. The kernel mapping idea is used to derive the
non-linear version, Kernel Discriminant via Support Vectors (SVKD).
In SVDA, only support vectors are involved to obtain the
transformation matrix. Thus, the computational complexity can be
greatly reduced for kernel based feature extraction. Experiments
carried out on several standard databases show a clear improvement
on LDA-based recognition Platform: |
Size: 2048 |
Author:sofi |
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Description: How to install the libsvm for MATLAB on Unix machine
Linear-kernel SVM for binary classification
kernel SVM for binary classification
cross validation for C and Gamma
multi-class SVM: one-vs-rest (OVR)
More ready-to-use matlab example
Available matlab codes to download Platform: |
Size: 1572864 |
Author:hoangthom |
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Description: 这是一个多分类程序，采用DAGSVM的方法，可用于初学者参考学习。(it's a matlab code for a multi-class SVM,which designed by DAGSVM. It is usefull for learners study .) Platform: |
Size: 1024 |
Author:小月亮晓儿
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Search - svm multi class matlab