Lasso回归是一种用于线性回归模型的正则化方法,它通过加入L1惩罚项来约束系数的大小,从而实现变量筛选和降维。与传统的最小二乘法不同,Lasso回归可以将某些系数压缩为零,从而将一些无关或冗余的变量排除在模型之外。这使得模型更简洁、稀疏,并提高了泛化能力。 2.2 变量筛选结果解读 在使用Lasso回归进行变量筛选后,我...
python lasso回归筛选变量 结果解读 c变量python lasso Lasso regression is a popular method used for variable selection in Python. It is particularly useful when dealing with datasets that have a large number of variables. In this response, we will discuss the resultsinterpretation specific to the ...