Description: SVM方法的基本思想是:定义最优线性超平面,并把寻找最优线性超平面的算法归结为求解一个凸规划问题。进而基于Mercer核展开定理,通过非线性映射φ,把样本空间映射到一个高维乃至于无穷维的特征空间(Hilbert空间),使在特征空间中可以应用线性学习机的方法解决样本空间中的高度非线性分类和回归等问题。svm 程序,即支持向量机的代码。-The basic idea of SVM method are: the definition of the optimal linear hyperplane, and the search algorithm for optimal linear hyperplane by solving a convex programming problem. Then based on Mercer nuclear expansion theorem, through a nonlinear mapping φ, the sample space is mapped to a high-dimensional and even infinite dimensional feature space (Hilbert space), so that in the feature space can be applied to solve the linear learning machine method, the sample space The highly nonlinear classification and regression problems. svm procedures that support vector machine code. Platform: |
Size: 117760 |
Author:秀 |
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Description: 于BP网络的权值优化是一个无约束优化问题,而且权值要采用实数编码,所以直接利用Matlab遗传算法工具箱。以下贴出的代码是为一个19输入变量,1个输出变量情况下的非线性回归而设计的,如果要应用于其它情况,只需改动编解码函数即可。-BP network weights optimization is a constrained optimization problem, and the right value to real-coded, so the direct use of the Matlab genetic algorithm toolbox. The code posted below is a 19 input variables, a nonlinear regression in the case of the output variable designed to be applied to other circumstances, only changes to the encoding and decoding functions can be. Platform: |
Size: 4096 |
Author:fuhai |
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Description: 用MATLAB实现自适应神经模糊推理系统(ANFIS)结构训练。代码中,首先创建一个初始原ANFIS结构,然后采用遗传算法(GA)、粒子群优化(PSO)来训练ANFIS。此进化训练算法可用于解决非线性回归函数逼近问题。-Implementation of adaptive neural fuzzy inference system (ANFIS) based on MATLAB. Code, the first to create an initial original ANFIS structure, and then using the genetic algorithm (GA), particle swarm optimization (PSO) to train ANFIS. This evolutionary training algorithm can be used to solve the nonlinear regression function approximation problem. Platform: |
Size: 21504 |
Author:张贝 |
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