cox redzone

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sparsity constraint sparse constraint detailedIntroduction: A linear model is a model that we often use, such as: In the text classification, bag-of-words has P = K features, a total of N = 5K text sample, in the image to blur, image classification, there are p=65k pixel features, n=100 samples; and so on. We can use linear models to solve these problems, such as linear regression, logistic regression, Cox regression. Because P is far greater than N,

reduced to 297. Zerovar=nearzerovar (MDRRDESCR)Newdata1=mdrrdescr[,-zerovar] Another class that needs to be removed is a variable that is strongly related to other arguments, and the corresponding command is findcorrelation. There may also be multiple collinearity problems in the arguments, which can be found using the Findlinearcombos command. The self-variable is reduced to 94 after this processing.Descrcorr = Cor (NEWDATA1)Highcorr = Findcorrelation (Descrcorr, 0.90)Newdata2 = newdata1[,-hig