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OSR.rar
- 气象上常用的最优子集回归，用fortran写的程序,Weather on the commonly used optimal subset regression using fortran written procedures
OSR
- 这个程序是一个计算所有可能的子集回归和用双评分准则选择最优回归的方法 -this is a program for calculating all possible subset regressions and selecting a optimal regression by couple score criterion
osr-python
- 写了一堆高仿Fortran最优子集回归算法的python代码，现分享出来，如果有用得着的就拿去用吧，避免纠结python3在win7环境下调用fortran程序这么些跟系统兼容相关程度高 的问题(I wrote a bunch of Python codes that imitate Fortran's optimal subset regression algorithm. Now share them. If you can use them, you can use them, avoid
CARS_PLS
- 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
cars
- 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。(The competitive adaptive weight weighting algorithm (CARS) uses adaptive heavy weighted sampling (ARS) to select the wavelength points with large abs
CARS
- 用于matlab模式识别（分类和回归）的特征变量提取方法，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。(The method of feature variables extraction for matlab pattern recognition (classification and regression), competitive a
竞争性自适应重加权算法(CARS)
- 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。