R：绘制套索贝塔系数

Question

我用 R 写了这个套索代码，我得到了一些 beta 值：

#Lasso
library(MASS)
library(glmnet)
Boston=na.omit(Boston)
x=model.matrix(crim~.,Boston)[,-1]
rownames(x)=c()
y=as.matrix(Boston$crim)
lasso.mod =glmnet(x,y, alpha =1, lambda = 0.1)
beta=as.matrix(rep(0,19))
beta=coef(lasso.mod)
matplot(beta,type="l",lty=1,xlab="L1",ylab="beta",main="lasso")

我想在这样的情节中绘制贝塔：

但我不知道我可以使用 R 中的哪个 plot 函数来做到这一点。

Answer 1

我不明白你为什么不想使用 build-in glmnet 方法但是你当然可以重现其结果（此处使用 ggplot）。
您仍然需要模型对象来提取 lambda 值...

编辑： 添加了 Coefs vs L1 范数

重现您的最小示例

library(MASS)
library(glmnet)
#> Le chargement a nécessité le package : Matrix
#> Le chargement a nécessité le package : foreach
#> Loaded glmnet 2.0-13
library(ggplot2)
library(reshape)
#> 
#> Attachement du package : 'reshape'
#> The following object is masked from 'package:Matrix':
#> 
#>     expand

Boston=na.omit(Boston)
x=model.matrix(crim~.,Boston)[,-1]
y=as.matrix(Boston$crim)
lasso.mod =glmnet(x,y, alpha =1)
beta=coef(lasso.mod)

提取 coef 值并将它们转换为适合 ggplot 的长而整洁的形式

tmp <- as.data.frame(as.matrix(beta))
tmp$coef <- row.names(tmp)
tmp <- reshape::melt(tmp, id = "coef")
tmp$variable <- as.numeric(gsub("s", "", tmp$variable))
tmp$lambda <- lasso.mod$lambda[tmp$variable+1] # extract the lambda values
tmp$norm <- apply(abs(beta[-1,]), 2, sum)[tmp$variable+1] # compute L1 norm

使用 ggplot 绘图：coef 与 lambda

# x11(width = 13/2.54, height = 9/2.54)
ggplot(tmp[tmp$coef != "(Intercept)",], aes(lambda, value, color = coef, linetype = coef)) + 
    geom_line() + 
    scale_x_log10() + 
    xlab("Lambda (log scale)") + 
    guides(color = guide_legend(title = ""), 
           linetype = guide_legend(title = "")) +
    theme_bw() + 
    theme(legend.key.width = unit(3,"lines"))

同底图glmnet方法：

# x11(width = 9/2.54, height = 8/2.54)
par(mfrow = c(1,1), mar = c(3.5,3.5,2,1), mgp = c(2, 0.6, 0), cex = 0.8, las = 1)
plot(lasso.mod, "lambda", label = TRUE)

使用 ggplot 绘图：系数与 L1 范数

# x11(width = 13/2.54, height = 9/2.54)
ggplot(tmp[tmp$coef != "(Intercept)",], aes(norm, value, color = coef, linetype = coef)) + 
    geom_line() + 
    xlab("L1 norm") + 
    guides(color = guide_legend(title = ""), 
           linetype = guide_legend(title = "")) +
    theme_bw() + 
    theme(legend.key.width = unit(3,"lines"))

同底图glmnet方法：

# x11(width = 9/2.54, height = 8/2.54)
par(mfrow = c(1,1), mar = c(3.5,3.5,2,1), mgp = c(2, 0.6, 0), cex = 0.8, las = 1)
plot(lasso.mod, "norm", label = TRUE)

由 reprex package (v0.2.0) 创建于 2018-02-26。

R：绘制套索贝塔系数

R: Plotting lasso beta coefficients

r

machine-learning

regression

glmnet

lasso-regression