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.
LS-SVMlab1.5aw
- 最小二乘支持向量机MATLAB实现源代码,可以用于模式识别以及回归,DEMOCLASS是使用方法示例-least squares support vector machines MATLAB source code, can be used for pattern recognition and regression, DEMOCLASS example is the use of
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
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
Iapcir
- 最小二乘曲线拟合的一个类,用来实现一元线性回归的负荷预测
nihe
- 简单的讲,所谓拟合是指已知某函数的若干离散函数值{f1,f2,…,fn},通过调整该函数中若干待定系数f(λ1, λ2,…,λ3), 使得该函数与已知点集的差别(最小二乘意义)最小。如果待定函数是线性,就叫线性拟合或者线性回归(主要在统计中),否则叫作非线性拟合或者非线性回归。表达式也可以是分段函数,这种情况下叫作样条拟合。
预测
- 数据预测算法,主要是一元n次方程的回归预测实现。* 预测分析--本算法只适用于有明显线性趋势的数据 * 默认为一元二次曲线方程法 * * 本程序主要涉及有两个算法 * 1.用最小二乘原理找到线性方程组的系数和常数。 * 2.解线性方程组 * 本程序在解线性方程组中,由于考虑到收敛性问题未采用迭代法,而是采用Gauss-Jordan消去法来解决。-data prediction algorithm is mainly one yuan n equation forecast to achieve
4
- MATLAB程序, 半参数线性回归模型的最小二乘核估计 半参数线性回归模型的最小二乘正交序列估计。-MATLAB program, semi-parametric linear regression model of least squares kernel estimation Semiparametric least squares linear regression model orthogonal sequence estimation.
CorrectCarNoImageAndRegnize
- 一种车牌图像校正新方法 【摘要】因摄像机角度而造成的机动车牌图像倾斜会对其后继的字符分割与识别带来不利的影响。本文在分析了车牌倾斜模式的基础上,提出了一种基于最小二乘支持向量机(LS-SVM)的车牌图像倾斜校正新方法。通过LS-SVM线性回归算法求取坐标变换矩阵并对畸变图像进行旋转校正。主要方法:首先,将二值倾斜车牌图像中的像素转换为二维坐标样本,并构造图像数据集 再通过LS-SVM线性回归算法对该数据集进行回归,求取主要参数 最后,再由该参数转换为能反映图像倾斜方向的2维坐标变换矩阵。实验
HausdorffRegression
- Hausdorff回归的主要优点是不应该指定的错误(垂直,水平,方向正交...与普通最小二乘),它是相对于较少的距离平方敏感。-The main advantages of the Hausdorff regression are that one should not specify the direction of the errors (vertical, horizontal, orthogonal ... with the ordinary least squares) and tha
pls_copy
- 这是一个非线性回归偏最小二乘程序,输入因变量与自变量,输出为x,y的主成分与负荷因子与回归系数- Inputs: x x matrix y y matrix Outputs: t score for x p loading for x u score for y q loading for y b regression coefficient
lssvm
- 一个简单的lssvm程序,用与最小二乘的回归预测-A simple ls svm program, with the least-squares regression
cd4ef1.ZIP
- 具有NA误差项的多元回归模型中最小二乘估计的强相合性With NA errors in the multiple regression model of strong consistency of least square estimate-With NA errors in the multiple regression model of strong consistency of least square estimate
LS-SVMLab-v1.7(R2006a-R2009a)
- matlab中的ls-svm工具包,是最小二乘支持向量机算法,可用于解决非线性的回归问题。-ls-svm tool in the Matlab package, least squares support vector machine algorithm can be used to solve nonlinear regression problems.
libsvm-3.12
- matlab中的libsvm工具包,是smo支持向量机算法,可用于解决非线性的回归问题。区别于最小二乘支持向量机。-Matlab libsvm Kit is to smo support vector machine algorithm that can be used to solve nonlinear regression problems. Different from the least squares support vector machine.
program-of-support-vector-machine
- matlab中的标准svm程序源码,用于解决线性的回归问题,不能用于解决非线性,区别于最小二乘支持向量机。-svm program source code, standard Matlab is used to solve linear regression problems, can not be used to solve nonlinear, different from the least squares support vector machine.
mtl_reg_sim_complinearized
- 多元非线性回归——岭回归方法,比常规的最小二乘更适合数据量较大的优化问题-Multiple nonlinear regression- ridge regression method is more suitable than the conventional least squares optimization problem of the large amount of data
Desktop
- 自改的偏最小二乘和主元回归的比较程序和说明。对初学者有借鉴意义,是本人的作业-this code is reprogramed by myself, it is done by PLS and PCE. it s my homework.enjoy it!
LS_SVMlab
- 最小二乘支持向量机MATLAB实现源代码,可以用于模式识别以及回归-Least squares support vector machine MATLAB source code, can be used for pattern recognition and regression