R语言基于glmnet构建分类模型并可视化特征系数（coefficient）以及L1正则化系数（lambda）实战

# 导入测试数据集

data(BinomialExample)x <- BinomialExample$xy <- BinomialExample$y

# 构建模型并可视化系数

glmmod <- glmnet(x, y, alpha=1, family="binomial",lambda = logspace(-10, 1, 100))# Plot variable coefficients vs. shrinkage parameter lambda.plot(glmmod, xvar="lambda")abline(v = cv.glmnet(x,y,lambda = logspace(-10, 1, 100))$lambda.min, col = "black")