lasso-regression

How does glmnet compute the maximal lambda value?

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问题 The glmnet package uses a range of LASSO tuning parameters lambda scaled from the maximal lambda_max under which no predictors are selected. I want to find out how glmnet computes this lambda_max value. For example, in a trivial dataset: set.seed(1) library("glmnet") x <- matrix(rnorm(100*20),100,20) y <- rnorm(100) fitGLM <- glmnet(x,y) max(fitGLM$lambda) # 0.1975946 The package vignette (http://www.jstatsoft.org/v33/i01/paper) describes in section 2.5 that it computes this value as follows:

How does glmnet compute the maximal lambda value?

阅读更多关于 How does glmnet compute the maximal lambda value?

The glmnet package uses a range of LASSO tuning parameters lambda scaled from the maximal lambda_max under which no predictors are selected. I want to find out how glmnet computes this lambda_max value. For example, in a trivial dataset: set.seed(1) library("glmnet") x <- matrix(rnorm(100*20),100,20) y <- rnorm(100) fitGLM <- glmnet(x,y) max(fitGLM$lambda) # 0.1975946 The package vignette ( http://www.jstatsoft.org/v33/i01/paper ) describes in section 2.5 that it computes this value as follows: sx <- as.matrix(scale(x)) sy <- as.vector(scale(y)) max(abs(colSums(sx*sy)))/100 # 0.1865232 Which

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