UBC2018年夏季学期"Elements of Statistical Learning"资料

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英属哥伦比亚大学教授Matías  Salibián-Barrera的统计学习课程讲义
附件含详细规范的R语言代码
开头从线性回归->岭回归->lasso>-elastic net>-spline regression
参考书目有The Elements of Statistical Learning etc.
对回归分析和机器学习感兴趣的同学不要错过

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关键词：Statistical statistica statistic Learning Elements

感谢分享好资源。楼主注意了，只要不是魏特别的资源，一般不主张设置高价。提倡分离精神。

hylpy1 发表于 2019-6-26 16:55
感谢分享好资源。楼主注意了，只要不是魏特别的资源，一般不主张设置高价。提倡分离精神。

那我降到30吧 在同类型课程中 这个资料是非常不错的 例如讲spline 把函数一些参数的意义都讲明白了
你看这个甚至不用google或者baidu

Matías  Salibián-Barrera也是著作等身 有多篇顶会 具体水平 网上搜些文章一看便知

课程难度属于大学高年级-研究生的范围 前置课程:线性回归 R语言 概率论

rng_ 发表于 2019-6-26 15:39
英属哥伦比亚大学教授Matías  Salibián-Barrera的统计学习课程讲义
附件含详细规范的R语言代码
开头从线 ...

can you provide table of contents?

hifinecon 发表于 2019-6-26 17:48
can you provide table of contents?

Week 1 (L1): Review of Linear Regression<br>
Sections 2.1, 2.1.1, 2.1.2, 2.1.3, 2.2, 2.2.1 from [JWHT13]<br>
Sections 2.4 and 2.6 from [HTF09].<br>
Week 2 (L2/3): Goodness of Fit vs Prediction error, Cross Validation<br>
Sections 5.1, 5.1.1, 5.1.2, 5.1.3 from [JWHT13]<br>
Sections 7.1, 7.2, 7.3, 7.10 from [HTF09].<br>
Week 3 (L4/5): Correlated predictors, Feature selection, AIC<br>
Sections 6.1, 6.1.1, 6.1.2, 6.1.3, 6.2 and 6.2.1 from [JWHT13]<br>
Sections 7.4, 7.5 from [HTF09].<br>
Week 4 (L6/MT1): Ridge regression, LASSO, Elastic Net<br>
Sections 6.2 (complete) from [JWHT13]<br>
Sections 3.4, 3.8, 3.8.1, 3.8.2 from [HTF09]<br>
Week 5 (L7/8): Elastic Net, Smoothers (Local regression, Splines)<br>
Sections 7.1, 7.3, 7.4, 7.5, 7.6 from [JWHT13]<br>
Week 6 (L9/10): Curse of dimensionality, Regression Trees<br>
Sections 8.1, 8.1.1, 8.1.3, 8.1.4 from [JWHT13]<br>
Week 7 (L11/MT2): Bagging<br>
Sections 8.2, 8.2.1 from [JWHT13]<br>
Week 8 (L12/13): Classification, LDA, LQA, Logistic Regression<br>
Section 4.1, 4.2, 4.3, 4.4, 2.2.3 from [JWHT13]<br>
Week 9 (L14/15): Trees, Ensembles, Bagging<br>
Sections 8.1.2, 8.2.1 and 8.2.2 from [JWHT13]<br>
Week 10 (L16/MT3): Random Forests<br>
Sections 8.2.1 and 8.2.2 from [JWHT13]<br>
Week 11 (L17/18): Boosting, Neural Networks?<br>
Sections 8.2.3 from [JWHT13]<br>
Sections 10.1 - 10.10 (except 10.7), 11.3 - 11.5, 11.7 from [HTF09]<br>
Week 12 (L19/20): Unsupervised learning, K-means, model-based clustering<br>
Sections 10.3 from [JWHT13]<br>
Sections 13.2, 14.3 from [HTF09]<br>
Week 13 (L21/L22): Hierarchical clustering, Principal Components, Multidimensional Scaling<br>
Sections 10.2, 10.3 from [JWHT13]<br>
Sections 8.5, 14.3, 14.5.1, 14.8, 14.9 from [HTF09]

rng_ 发表于 2019-6-26 18:18
Week 1 (L1): Review of Linear Regression
Sections 2.1, 2.1.1, 2.1.2, 2.1.3, 2.2, 2.2.1 from [JWHT1 ...

thank you so much for this!

感谢分享好资源！