Description: PRINCIPLE: PLS cross-validation using the SIMPLS or WIMPLS algorithm, respectively for tall or wide X-data. The optimal approach is selected automatically. Platform: |
Size: 2048 |
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Description: 基于pls对光谱分析 包括数据读取，小波变换PCA分析，PLS建模，交叉验证-Pls include data on the spectrum based on reads, wavelet transform PCA analysis, PLS modeling, cross-validation Platform: |
Size: 4096 |
Author:liu |
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Description: 用于自动计算X和Y矩阵的PLS回归。生成的各种表格一XLS文件存储。其中交叉验证内置，但是可能会有问题-Used to automatically calculate the X and Y matrices PLS regression. A variety of forms generated XLS file storage. Where cross-validation built-in, but there may be a problem Platform: |
Size: 3072 |
Author:zhangxun |
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Description: 单因变量偏最小二乘回归matlab程序
程序尚不完善，固定提取了3个主成分，没有做寻求最佳主成分个数；没有做交叉有效性检验
-Single dependent variable and partial least squares regression matlab
The program is not perfect, the fixed extract 3 principal components, do not seek the best number of principal components do not cross validation test Platform: |
Size: 1024 |
Author:mali |
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Description: 交叉验证(Cross-validation)主要用于建模应用中，例如PCR 、PLS 回归建模中。在给定的建模样本中，拿出大部分样本进行建模型，留小部分样本用刚建立的模型进行预报，并求这小部分样本的预报误差，记录它们的平方加和。这个过程一直进行，直到所有的样本都被预报了一次而且仅被预报一次。把每个样本的预报误差平方加和，称为PRESS(predicted Error Sum of Squares)-Cross-validation, sometimes called rotation estimation,[1][2][3] is a model validation technique for assessing how the results of a statistical analysis will generalize to an independent data set. It is mainly used in settings where the goal is prediction, and one wants to estimate how accurately a predictive model will perform in practice. In a prediction problem, a model is usually given a dataset of known data on which training is run (training dataset), and a dataset of unknown data (or first seen data) against which the model is tested (testing dataset).[4] The goal of cross validation is to define a dataset to test the model in the training phase (i.e., the validation dataset), in order to limit problems like overfitting, give an insight on how the model will generalize to an independent dataset (i.e., an unknown dataset, for instance a real problem), etc. Platform: |
Size: 4096 |
Author:liufengfeng |
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Description: 竞争性自适应重加权算法（CARS）是通过自适应重加权采样（ARS）技术选择出PLS模型中回归系数绝对值大的波长点，去掉权重小的波长点，利用交互验证选出RMSECV指最低的子集，可有效寻出最优变量组合。(Competitive adaptive reweighted algorithm (CARS) is obtained by adaptive reweighted sampling (ARS) technique is selected in the PLS model regression coefficients with large absolute values of wavelength, remove the weight of small wavelength, using cross validation to select the RMSECV refers to the minimum subset, can effectively find out the optimal combination of variables.) Platform: |
Size: 1453056 |
Author:李木木木木 |
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