Description: 模式识别matlab工具箱,包括SVM,ICA,PCA,NN等等模式识别算法,很有参考价值-pattern recognition Matlab toolbox, including SVM, ICA, PCA, NN pattern recognition algorithms, and so on, of great reference value Platform: |
Size: 630784 |
Author:zsq |
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Description: 一种很容易理解的svm matlab工具箱，可用于分类，回归，并附很多示例。-A very easy to understand svm matlab toolbox, can be used for classification, regression, together with many examples. Platform: |
Size: 340992 |
Author:徐杰 |
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Description: 一种很容易理解的svm matlab工具箱,可用于分类，回归，并附有很多示例。-A very easy to understand svm matlab toolbox, can be used for classification, regression, together with many examples. Platform: |
Size: 4064256 |
Author:徐杰 |
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Description: 支持向量机的工具箱，对于图像处理中的分类识别学习者有着很大帮助。分享快乐！-SVM toolbox for image processing in the classification and identification of learners have a great help to me. To share their happiness! Platform: |
Size: 125952 |
Author:hq |
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Description: 这里实现了四种SVM工具箱的分类与回归算法-Here to realize the four SVM toolbox Classification and regression algorithm Platform: |
Size: 2706432 |
Author:李晋博 |
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Description: 这里实现了基于四种SVM工具箱的分类与回归算法:
1、工具箱：LS_SVMlab
Classification_LS_SVMlab.m - 多类分类
Regression_LS_SVMlab.m - 函数拟合
2、工具箱：OSU_SVM3.00
Classification_OSU_SVM.m - 多类分类
3、工具箱：stprtool\svm
Classification_stprtool.m - 多类分类
4、工具箱：SVM_SteveGunn
Classification_SVM_SteveGunn.m - 二类分类
Regression_SVM_SteveGunn.m - 函数拟合
更详细的相关函数说明请通过help命令查看！-Here the realization of the four SVM toolbox based on the classification and regression algorithm: 1, Toolbox: LS_SVMlabClassification_LS_SVMlab.m- Multiclass Classification Regression_LS_SVMlab.m- function fitting 2, the toolbox: OSU_SVM3.00Classification_OSU_SVM.m- Multiclass Classification 3, Toolbox: stprtoolsvmClassification_stprtool.m- Multiclass Classification 4 toolbox: SVM_SteveGunnClassification_SVM_SteveGunn.m- II Category Regression_SVM_SteveGunn.m- function fitting a more detailed explanation of the correlation function through the help command to view! Platform: |
Size: 2740224 |
Author:杨愚根 |
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Description: 这里实现了四种SVM工具箱的分类与回归算法
1、工具箱：LS_SVMlab
Classification_LS_SVMlab.m - 多类分类
Regression_LS_SVMlab.m - 函数拟合
2、工具箱：OSU_SVM3.00
Classification_OSU_SVM.m - 多类分类
3、工具箱：stprtool\svm
Classification_stprtool.m - 多类分类
4、工具箱：SVM_SteveGunn
Classification_SVM_SteveGunn.m - 二类分类
Regression_SVM_SteveGunn.m - 函数拟合
觉得好就帮我顶一下帖子，要不沉了！
-Here to realize the four SVM toolbox Classification and Regression Algorithm 1, Toolbox: LS_SVMlabClassification_LS_SVMlab.m- Multiclass Classification Regression_LS_SVMlab.m- function fitting 2, the toolbox: OSU_SVM3.00Classification_OSU_SVM.m- Multiclass Classification 3, Toolbox : stprtoolsvmClassification_stprtool.m- Multiclass Classification 4, Toolbox: SVM_SteveGunnClassification_SVM_SteveGunn.m- II Category Regression_SVM_SteveGunn.m- function fitting to help me feel good on top of you post, or heavy! Platform: |
Size: 232448 |
Author:fgqqd |
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Description: 这是处理图像分类的最小二乘法svm工具箱，里面有详细的使用说明，功能强大，欢迎下载使用。-This is the deal with image classification of least squares SVM toolbox, which has detailed instructions and powerful are welcome to download. Platform: |
Size: 224256 |
Author:tang |
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Description: 很好用的svm工具箱，dagsvm对于图像分类效果非常好，分类精度很高，代码清洗简单。-Good use of SVM Toolbox, dagsvm for image classification effect is very good, very high classification accuracy, code cleaning easy. Platform: |
Size: 5120 |
Author:tang |
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Description: matlab图像处理工具相，使用了主成分分析，ANN，SVM等方法。-This toolBox used in the image processing(feature extraction and classification)
PCA,LDA,ICA,DCT,RBF,RBE,GRNN,KNN,minimum distance,SVM, and others Platform: |
Size: 74752 |
Author:大长今 |
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Description: 支持向量机的研究现已成为机器学习领域中的研究热点，其理论基础是Vapnik[3]等提出的统计学习理论。统计学习理论采用结构风险最小化准则，在最小化样本点误差的同时，缩小模型泛化误差的上界，即最小化模型的结构风险，从而提高了模型的泛化能力，这一优点在小样本学习中更为突出。SVM理论正是在这一基础上发展而来的，经过十几年的研究和发展，已开始逐步应用于一些领域。在解决小样本、非线性及高维模式识别问题中表现出许多特有的优势，已经在模式识别、函数逼近和概率密度估计等方面取得了良好的效果。- Support Vector Machine (SVM) is a new machine learning technique in recent years developed based on statistical learning theory (SLT). It wins popularity due to many attractive features and emphatically performance in the fields of nonlinear and high dimensional pattern recognition. The theory and algorithm of SVC is studied at first, then, simulation is to recognize handwritten numeral with the Lib-SVM toolbox. At last, we study the result, which shows that the SVC can do the classification problem with good performance, shorter operation time and is more suitable for real-time implementation. Platform: |
Size: 1155072 |
Author:任修齐 |
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