October 2021
Intermediate to advanced
289 pages
8h 31m
Chinese
Content preview from 数据科学中的实用统计学(第2版)
Become an O’Reilly member and get unlimited access to this title plus top books and audiobooks from O’Reilly and nearly 200 top publishers, thousands of courses curated by job role, 150+ live events each month,
O’Reilly covers everything we've got, with content to help us build a world-class technology community, upgrade the capabilities and competencies of our teams, and improve overall team performance as well as their engagement.I wanted to learn C and C++, but it didn't click for me until I picked up an O'Reilly book. When I went on the O’Reilly platform, I was astonished to find all the books there, plus live events and sandboxes so you could play around with the technology.I’ve been on the O’Reilly platform for more than eight years. I use a couple of learning platforms, but I'm on O'Reilly more than anybody else. When you're there, you start learning. I'm never disappointed.I'm always learning. So when I got on to O'Reilly, I was like a kid in a candy store. There are playlists. There are answers. There's on-demand training. It's worth its weight in gold, in terms of what it allows me to do.
统计机器学习
｜
231
subsample
和
colsample_bytree
使用无放回方式抽取出的记录比例以及在拟合树时抽取出的预测变量的比例。与随
机森林类似，这些参数也有助于避免过拟合，它们的默认值是
1.0
。
lambda/reg_lambda
和
alpha/reg_alpha
用于控制过拟合的正则化参数（参见
6.4.3
节）。在
Python
中，默认值为
reg_
lambda=1
和
reg_alpha=0
。在
R
中，这两个值都默认为
0
。
本节要点
•
提升方法是一类集成模型，它的基本方法是拟合一系列模型，并在连续轮次中赋予
那些误差较大的记录更大的权重。
•
随机梯度提升是最常用的一种提升方法，性能也最好。使用树模型的随机梯度提升
是最普遍的一种形式。
• XGBoost
是一种非常流行的随机梯度提升软件包，它的计算效率非常高。数据科学
的常用语言中都提供了这个软件包。
•
提升方法容易对数据过拟合，需要调整超参数来避免过拟合。
•
正则化是避免过拟合的一种方法，它包含一个惩罚项，这个惩罚项是关于模型中参
数的数量（如树的大小）的。
•
交叉验证对于提升方法尤其重要，因为提升方法需要设定大量的超参数。
6.5
小结
本章介绍了两种分类和预测方法，它们不是从一个拟合了整个数据集的结构化模型（如
一个线性回归）开始，而是在数据中进行局部的、灵活的“学习”。
KNN
是
一种非常简
单的过程，它找出类似的记录，并将其中的多数类（或平均值）赋给要预测的记录。树
模型则尝试了预测变量的各种分割值，以迭代方式不断地将数据分割成多个部分，而这 ...
Become an O’Reilly member and get unlimited access to this title plus top books and audiobooks from O’Reilly and nearly 200 top publishers, thousands of courses curated by job role, 150+ live events each month,
and much more.
Read now
Unlock full access
More than 5,000 organizations count on O’Reilly
O’Reilly covers everything we've got, with content to help us build a world-class technology community, upgrade the capabilities and competencies of our teams, and improve overall team performance as well as their engagement.Julian F.
I wanted to learn C and C++, but it didn't click for me until I picked up an O'Reilly book. When I went on the O’Reilly platform, I was astonished to find all the books there, plus live events and sandboxes so you could play around with the technology.Addison B.
I’ve been on the O’Reilly platform for more than eight years. I use a couple of learning platforms, but I'm on O'Reilly more than anybody else. When you're there, you start learning. I'm never disappointed.Amir M.
I'm always learning. So when I got on to O'Reilly, I was like a kid in a candy store. There are playlists. There are answers. There's on-demand training. It's worth its weight in gold, in terms of what it allows me to do.