Description: Ridge Regression RR 岭回归估计，是非常有用的非线性时间序列算法，在局部多项式预测中非常有用。-Ridge Regression RR ridge regression estimates, it is useful to nonlinear time series algorithms, in Local Polynomial prediction in very useful. Platform: |
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Author:zhxj |
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Description: Code for computing LORETA inverse solution for the EEG/MEG inverse problem.This corresponds to a Ridge regression using a discrete Laplace Operator as the prior covariance structure of the coeficients. The code is open to use different design matrices and covariance operator. Platform: |
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Author:Puestejo |
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Description: In kernel ridge regression we have seen the final solution was not sparse in the variables ® .
We will now formulate a regression method that is sparse, i.e. it has the concept of support
vectors that determine the solution.
The thing to notice is that the sparseness arose from complementary slackness conditions
which in turn came from the fact that we had inequality constraints. In the SVM the penalty
that was paid for being on the wrong side of the support plane was given by C
P
i » k
i for
positive integers k, where » i is the orthogonal distance away from the support plane. Note
that the term jjwjj2 was there to penalize large w and hence to regularize the solution.
Importantly, there was no penalt Platform: |
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Author:bahman |
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Description: This matlab code for estimating the static linear system with Ridge Regression that is written by matlab 7.0.
Here we want to estimate the below function:
1 - u^2 + 2*u^3 +u^5 +3*u^7
these are 2 files : without noise and with noise
finally,there are plots for showing results.
-This is matlab code for estimating the static linear system with Ridge Regression that is written by matlab 7.0.
Here we want to estimate the below function:
1 - u^2 + 2*u^3 +u^5 +3*u^7
these are 2 files : without noise and with noise
finally,there are plots for showing results.
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Author:maysam |
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Description: 岭回归的matla源程序，主要用于解决无法求逆或需要更好的解时所用的-Ridge regression matla source, mainly used to solve the inverse can not be a better solution or need to use when Platform: |
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Author:吴蓉 |
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Description: This just a simple method in element of statistical learning..... It is a function for degree of freedom calculation.(Using for ridge regression)
-This is just a simple method in element of statistical learning..... It is a function for degree of freedom calculation.(Using for ridge regression)
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Author:baifan |
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Description: Applied Statistics Using SPSS,STATISTICA,MATLAB and R
Joaquim P.
ISBN 978-3-540-71971-7 Springer Berlin Heidelberg New York-Applied Statistics Using SPSS, STATISTICA,MATLAB and R
Inclusion of R as an application tool. As a matter of fact, R is a free
software product which has nowadays reached a high level of maturity
and is being increasingly used by many people as a statistical analysis
tool.
Chapter 3 has an added section on bootstrap estimation methods, which
have gained a large popularity in practical applications.
A revised explanation and treatment of tree classifiers in Chapter 6 with
the inclusion of the QUEST approach.
Several improvements of Chapter 7 (regression), namely: details
concerning the meaning and computation of multiple and partial
correlation coefficients, with examples a more thorough treatment and
exemplification of the ridge regression topic more attention dedicated to
model evaluation. Platform: |
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Author:ABC |
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Description: 这段代码可以实现机器学习中的岭回归。自行添加高斯噪声后对每个数据集的七阶多项式用不同的值λ进行岭回归-Perform ridge regression on each dataset with 7th order polynomial with different value λ.Add Gaussian noise. Platform: |
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Author:yuanxin |
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Description: 岭回归(英文名：ridge regression, Tikhonov regularization)是一种专用于共线性数据分析的有偏估计回归方法，实质上是一种改良的最小二乘估计法，通过放弃最小二乘法的无偏性，以损失部分信息、降低精度为代价获得回归系数更为符合实际、更可靠的回归方法，对病态数据的拟合要强于最小二乘法。
总之，本文档是岭回归的R语言实现代码，主要用于解决当模型中出现多重共线性问题，尤其是当你所有的解释变量都很重要，又无法通过其他检验来删除时，岭回归是一个很好的解决办法。(Ridge regression (English Name: ridge regression, Tikhonov regularization) is a kind of special linear data analysis of biased estimation is actually the least squares regression method, an improved estimation method, the unbiased least square method to give up the part of the loss of information, reduce the accuracy of regression coefficient is more practical more reliable, the cost of pathological data was stronger than that of least squares fitting.
In short, this document is a ridge regression of the R language code, mainly used to solve the multicollinearity problems when the model, especially when you have all the explanatory variables are very important, and not by other inspection to delete, ridge regression is a good solution.) Platform: |
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Author:jingxuanjuan
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