From d3195b8d58c7eb613a26a10ad1612b5e842a8d7d Mon Sep 17 00:00:00 2001 From: shataowei Date: Wed, 20 Nov 2019 16:42:44 +0800 Subject: [PATCH] =?UTF-8?q?gbdt=E6=AD=A3=E5=88=99=E5=8C=96?= MIME-Version: 1.0 Content-Type: text/plain; charset=UTF-8 Content-Transfer-Encoding: 8bit --- .idea/workspace.xml | 44 ++++++++++++++++++++++---------------------- README.md | 2 +- 2 files changed, 23 insertions(+), 23 deletions(-) diff --git a/.idea/workspace.xml b/.idea/workspace.xml index 86945cc..cd122fb 100644 --- a/.idea/workspace.xml +++ b/.idea/workspace.xml @@ -2,7 +2,7 @@ - + @@ -23,7 +23,7 @@ - + @@ -36,8 +36,8 @@ - - + + @@ -47,12 +47,12 @@ - + - - + + @@ -113,8 +113,8 @@ @@ -1352,20 +1352,20 @@ - - + + - - + + - + - - + + @@ -1374,20 +1374,20 @@ - - + + - - + + - + - - + + diff --git a/README.md b/README.md index 509600a..ceb45b2 100644 --- a/README.md +++ b/README.md @@ -227,7 +227,7 @@ - [即便拟合负梯度是可行的,为什么不直接拟合残差? 拟合负梯度好在哪里](机器学习/集成学习/GBDT.md#L164) - [Shrinkage收缩的作用](机器学习/集成学习/GBDT.md#L164) - [feature属性会被重复多次使用么](机器学习/集成学习/GBDT.md#L164) - - [如何进行子采样的](机器学习/集成学习/GBDT.md#L164) + - [gbdt如何进行正则化的](机器学习/集成学习/GBDT.md#L164) - [为什么集成算法大多使用树类模型作为基学习器?或者说,为什么集成学习可以在树类模型上取得成功](机器学习/集成学习/GBDT.md#L164) - [gbdt的优缺点](机器学习/集成学习/GBDT.md#L164) - [gbdt和randomforest区别](机器学习/集成学习/GBDT.md#L164)