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4下载：
在matlab平台下，用GA对的lssvm的参数进行优化，很有用的东西。-Platform in matlab, using the GA to optimize parameters lssvm, very useful things.
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这是两篇非常好的讲怎么样对SVM的参数优化，可以从中学习进而对SVM算法改进-This is two very good speakers on how to optimize the SVM parameters, you can learn and thus improve the SVM algorithm
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利用遗传基因算法对SVM-RFE算法进行优化，从而获取更优异的特征，提高检测率，该算法的SVMtrain利用matlab自带的函数-The use of genetic algorithms to optimize the SVM-RFE algorithm, in order to gain more excellent features, improve the detection rate of the algorithm using matlab comes SVMtrain funct
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以优化SVM算法的参数c和g为例，对FA（萤火虫算法）MATLAB源码进行了逐行中文注解。是很好的学习材料。-
SVM algorithm to optimize the parameters c and g as an example, FA (firefly algorithm) MATLAB source was progressive Chinese annotations. It is a good learning materials.
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以优化SVM算法的参数c和g为例，对GWO算法MATLAB源码进行了逐行中文注解。 是很好的学习材料。-SVM algorithm to optimize the parameters c and g, for example, for GWO algorithm MATLAB source was progressive Chinese annotations. It is a good learning materials.
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以优化SVM算法的参数c和g为例，对CS算法MATLAB源码进行了逐行中文注解。-SVM algorithm to optimize the parameters c and g, for example, the CS algorithm MATLAB source was progressive Chinese annotations.
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以优化SVM算法的参数c和g为例，对GSA（引力搜索算法）MATLAB源码进行了详细中文注解。是很好的学习材料。-
In order to optimize SVM algorithm parameters c and g as an example, the GSA (Gravitational Search Algorithm) MATLAB source code for a detailed Chinese annotation. Is a good learning materia
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主要是利用CLO对svm进行优化，并能进行预测的matlab程序，可以运行出来，供参考-CLO is mainly used to optimize the SVM, and can predict the matlab program, you can run out for reference
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以优化SVM算法的参数c和g为例，使用狼群算法进行优化(Taking the parameters c and g of the optimized SVM algorithm as an example, we optimize it with a wolf group algorithm)
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模拟退火算法的代码以及使用模拟退火法寻优SVM中的参数c和g(The code of simulated annealing algorithm and the use of simulated annealing to optimize the parameters c and G in SVM)
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GA优化算法优化支持向量机的惩罚参数c和核函数的gamma。(GA optimization algorithm is used to optimize the penalty parameters c and kernel function gamma of SVM.)
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利用粒子群优化算法对支持向量机中的核函数参数和惩罚参数进行优化是非常有效的手段，可以大大提高鲁棒性。实际过程中读者可通过下载我上传的代码，简单进行修改和阅读附件论文即可快速掌握相关方面的知识，快速使用这一方法。(Particle swarm optimization (PSO) is a very effective method to optimize the kernel function parameters and penalty parameters of SVM, which can
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