Question

我在matlab中搜索有效的逻辑回归实现。我在matlab中使用了lassoglm。但是当我尝试10000个具有1000个特征和正则化参数0.005到1的示例时，它确实很慢。我使用双折交叉验证。从lambda 0.05开始，它非常慢，需要花费很多时间。

有没有更好的方法？

Answer 1

您可能想查看LIBLINEAR。它是一个免费的，最先进的线性大规模学习库。它有一个MATLAB接口。

LIBLINEAR有几种线性方法，包括：

 for multi-class classification
     0 -- L2-regularized logistic regression (primal)
     1 -- L2-regularized L2-loss support vector classification (dual)
     2 -- L2-regularized L2-loss support vector classification (primal)
     3 -- L2-regularized L1-loss support vector classification (dual)
     4 -- support vector classification by Crammer and Singer
     5 -- L1-regularized L2-loss support vector classification
     6 -- L1-regularized logistic regression
     7 -- L2-regularized logistic regression (dual)
   for regression
    11 -- L2-regularized L2-loss support vector regression (primal)
    12 -- L2-regularized L2-loss support vector regression (dual)
    13 -- L2-regularized L1-loss support vector regression (dual)

在matlab中使用L1正则化进行有效逻辑回归

1 个答案: