Description: psotoolbox程序已经通过了测试函数，可用来进行svm或ann的参数优化
-psotoolbox process has passed the test function, can be used to carry out or ann SVM Parameter Optimization Platform: |
Size: 97280 |
Author:徐冲 |
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Description: 经典的支持向量机SVM用于分类的MATLAB程序,可用于辨识,分类和参数优化!-Classical SVM support vector machine for classification of MATLAB procedures, can be used for identification, classification and parameter optimization! Platform: |
Size: 2048 |
Author:ncepu_ly |
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Description: libsvm的参数寻优程序。针对SVR提供full gridsearch方式的参数寻优，主要用于SVM回归预测-libsvm optimization process parameters. Provide full gridsearch for SVR parameter optimization approach, mainly used for SVM regression prediction Platform: |
Size: 2048 |
Author:张瑞 |
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Description: 用遗传算法进行特征选取和svm参数优化的程序。遗传算法工具箱goat已在压缩包 需要安装libsvm就可以直接运行。数据集采用UCI中的german数据集，并完成归一化操作-Genetic algorithm with feature selection and parameter optimization svm procedures. Genetic Algorithm Toolbox in goat need to install libsvm package can be run directly. UCI data sets used in the german data set, and complete normalization operation Platform: |
Size: 139264 |
Author:覃茂运 |
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Description: 这是一个用pso优化SVM中的惩罚参数C和核参数g的MATLAB源码，简单易学-This is an optimization of SVM with the pso in the penalty parameter C and kernel parameter g of the MATLAB source code, easy to learn Platform: |
Size: 1024 |
Author:yyifang |
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Description: SVM回归中用的gridregression.py函数，用它来进行参数寻优，做了一些改动适用于windows。-SVM regression using the gridregression.py function, use it to carry out parameter optimization, has done some changes to apply to windows. Platform: |
Size: 3072 |
Author:wangpw |
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Description: A distributed PSOSVM hybrid system with feature selection and parameter optimization
-Abstract
This study proposed a novel PSO–SVM model that hybridized the particle swarm optimization (PSO) and support vector machines (SVM) to
improve the classification accuracy with a small and appropriate feature subset. This optimization mechanism combined the discrete PSO with the
continuous-valued PSO to simultaneously optimize the input feature subset selection and the SVM kernel parameter setting. The hybrid PSO–SVM
data mining system was implemented via a distributed architecture using the web service technology to reduce the computational time. In a
heterogeneous computing environment, the PSO optimization was performed on the application server and the SVM model was trained on the
client (agent) computer. The experimental results showed the proposed approach can correctly select the discriminating input features and also
achieve high classification accuracy.
# 2007 Elsevier B.V. All rights reserved. Platform: |
Size: 565248 |
Author:alice |
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Description: SVM神经网络中的参数优化---利用SVM提升分类器性能，很好-Parameter optimization of SVM neural network--- SVM to enhance the performance of the classifier, good Platform: |
Size: 3072 |
Author:suua |
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Description: 由于遗传算法具有隐含的并行性和强大的全局搜索能力,可以在很短的时间内搜索到全局最优点。使用GA对SVM进行参数的优化,寻找最优的惩罚因子和SVM中RBF参数的组合。结合RBF参数r和惩罚因子C, 可以得到需要优化的参数组合。希望对大家有用！-Genetic algorithm with implicit parallelism and powerful global search capability, you can search within a very short period of time to the global optimum. GA parameter optimization of SVM, to find the optimal penalty factor and SVM RBF parameter combinations. Combination of the the RBF parameters of r and the penalty factor C, can be a combination of parameters that need to be optimized. I hope useful for all of us! Platform: |
Size: 8192 |
Author:张琪 |
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Description: SVM神经网络中的参数优化---提升分类器性能,模型精度较高-SVM neural network classifier parameter optimization--- to enhance performance, high accuracy of the model Platform: |
Size: 284672 |
Author:wang yu |
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Description: SVM的参数优化——如何更好的提升分类器的性能，含有源程序和代码(SVM parameter optimization - how to better improve the performance of the classifier, containing source code and code) Platform: |
Size: 208896 |
Author:潇潇飒飒 |
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Description: 将改进的粒子群算法和GA与SVM相结合，通过参数寻优构建新模型完成对空气质量指数的预测(The improved particle swarm optimization and genetic algorithm are combined with SVM. The prediction of air quality index (AQI) is completed by constructing a new model by parameter optimization.) Platform: |
Size: 19456 |
Author:心静2279 |
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Search - SVM parameter optimization