搜索资源列表
Regpyrim
- 使用最小二乘支持向量机对多维pyrim数据进行回归，需要下载最小二乘支持向量机工具箱。-use of least squares support vector machines for multidimensional data pyrim return need to download least squares support vector machines toolbox.
ridgeregresssvm
- 最小二乘支持向量机岭回归函数,可以进行预测和分类-least squares support vector machine regression function Ridge, forecasts and classification
denoise_kpca
- 最小二乘支持向量机岭回归函数,可以进行预测和分类-least squares support vector machine regression function Ridge, forecasts and classification
Spider4dataanlysis
- ?Spider-matlab工具箱，为一良好的数据分析工具箱，内建核偏最小二乘回归(KPLS),径向基网络回归(RBFnet)等；支持向量机(SVC)分类；聚类分析等．-Spider-Matlab Toolbox for a good data analysis toolbox. Built-nuclear partial least squares (PLS) regression neural network (RBFnet); Support Vector Machine (SVC) c
BDK-SOMPLS
- 有监督自组织映射-偏最小二乘算法(A supervised self-organising map–partial least squares algorithm),可以用语多变量数据的回归分析-supervised self-organizing map - Partial Least Squares (A supervised self-org anising map - partial least squares algorithm) , terms of the multi - var
LS_SVM最小二乘支持向量机Matlab源码
- 自编的最小二乘支持向量机Matlab代码，主要用于非线性回归
Inertiadevicefaultpredictionbasedonwavelet
- ：为了提高最小二乘支持向量回归机的性能，将Morlet小波核函数引入其中，形成了最小二乘小波支 持向量回归机模型。利用待优化的参数重构模型的目标函数和约束条件，并在此基础上通过遗传算法进行参数 选择，从而提高了该模型的泛化能力。将最小二乘小波支持向量回归机应用于导弹陀螺仪的漂移趋势预测，仿真 实验结果表明了该方法的有效性和可行性，因此可以为陀螺仪的故障预报、可靠性辅助决策提供依据。-To improve the ability of least square support vect
work
- 最小二乘支持向量机工具箱可用来分类 回归和预测很方便-this is a tool for the least vector machine,it can classier and regession.easy
PLS
- 偏最小二乘回归的通用程序，自己设置参数后即可运行。-The general procedure of partial least squares regression, can set their own parameters after operation.
PLS-regression
- 王惠文－（book）偏最小二乘回归方法及应用1 -Wang Huiwen- (book) and application of partial least squares regression method 1
IRWLS-SVR-code
- IRWLS-SVR即基于迭代加权最小二乘的支持向量机回归-IRWLS-SVR，Support vectors based on iteratively reweighted least squares
p
- PLS用于偏最小二乘回归计算,十分有用的源程序代码-PLS matlab
yaiqen-V2.4
- 最小二乘回归分析算法，模拟数据分析处理的过程，基于混沌的模拟退火算法。- Least-squares regression analysis algorithm, Analog data analysis processing, Chaos-based simulated annealing algorithm.
lssvm
- 最小二乘支持向量机回归，四个插入数据分别为训练输入、训练输出、测试输入、测试输出。工具包+程序(Least squares support vector regression (SVM), the four inserted data are training input, training output, test input and test output)
LSSVMlabv1_8_R2009b_R2011a
- 最小二乘支持向量机，功能（实现回归预测和分类）(least squares support vector machine)
chapter25
- 各类分析代码，可实现最小二乘普通回归的比较(Principal component regression)
5826
- 一个师兄的毕设，最小二乘回归分析算法，基于kaiser窗的双谱线插值FFT谐波分析。( A complete set of brothers, Least-squares regression analysis algorithm, Dual-line interpolation FFT harmonic analysis kaiser windows.)
lasso
- 线性回归里的最小二乘估计，以及应用坐标下降的岭回归和Lasso的回归的python实现(Ridge regression and Lasso regression)