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数据科学中的实用统计学(第2版)
book

数据科学中的实用统计学(第2版)

by Peter Bruce, Andrew Bruce, Peter Gedeck
October 2021
Intermediate to advanced
289 pages
8h 31m
Chinese
Posts & Telecom Press
Content preview from 数据科学中的实用统计学(第2版)
分类
|
193
•
如果想了解更多关于
SMOTE
算法的知识,可以参考
Nitesh V. Chawla
、
Kevin W. Bowyer
、
Lawrence O. Hall
和
W
. Philip Kegelmeyer
的文章:“
SMOTE: Synthetic Minority Over-
sampling Technique
”。
•
也可以参考
Analytics V
idhya Content Team
的文章:“
Practical Guide to Deal with Imbalanced
Classification Problems in R
”。
5.6
 小结
分类是预测记录属于两种(或更多)类别中哪一个的过程,它是预测性分析的一种基本工
具。一项贷款会违约吗(“是”还是“否”)?会提前偿还吗?网站访问者会点击这个链接
吗?会购买东西吗?一项保险索赔是否是诈骗?在分类问题中,我们通常只对某一个类别
感兴趣(例如欺诈性的保险索赔)。在二元分类中,通常将这种类别设置为
1
,而将另一个
更普遍的类别设置为
0
。一般来说
,分类过程的关键环节是估计一个
倾向分数
,即一条记
录属于我们感兴趣的类别的概率。一种常见的分类情形是,我们感兴趣的类别中的记录数
量非常稀少。在评估一个分类器时,除了简单的准确率之外,还有很多模型评估指标,它
们在稀有类情况下非常重要,这时候将所有记录分类为
0
可以得到很高的准确率。
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Publisher Resources

ISBN: 9787115569028