修改5.LR文档

2026-06-30 02:06:14 +08:00 · 2017-09-14 23:52:41 +08:00
parent 9d2ef5fdaa
commit 3ab442bfab
2 changed files with 4 additions and 0 deletions
--- a/docs/5.Logistic回归.md
+++ b/docs/5.Logistic回归.md
@@ -245,6 +245,10 @@ def gradAscent(dataMatIn, classLabels):
    return array(weights)
 ```

+大家看到这儿可能会有一些疑惑，就是，我们在迭代中更新我们的回归系数，后边的部分是怎么计算出来的？为什么会是 alpha * dataMatrix.transpose() * error ?因为这就是我们所求的梯度，也就是对 f(w) 对 w 求一阶导数。具体推导如下:
+
+![f(w)对w求一阶导数](../images/5.Logistic/LR_21.png)
+
 > 测试算法: 使用 Logistic 回归进行分类

 ```python
--- a/images/5.Logistic/LR_21.png
+++ b/images/5.Logistic/LR_21.png