Statistical Learning统计学习

【课程名称】Statistical Learning统计学习

【课程级别】本科生

【授课学校】莱斯大学，统计学系

【教学小组】Genevera Allen

【课程介绍】

This course is a survey of data mining and statistical learning techniques and will be comprised of three parts: 1) Linear methods for supervised learning; 2) Unsupervised learning techniques; and 3) Non-linear and Ensemble methods. Topics covered include ridge regression, lasso, discriminant analysis, support vector machines, splines, kernel methods, boosting, classification and regression trees, matrix factorizations, clustering, principal components analysis, cross-validation, random forests, and graphical models. Students will learn how to use each method, when the method should be applied, and its strengths and weaknesses.

【教学资源】

此课程有 48 个资源,分类如下:

教学大纲1

教师简历1

讲义26

作业6

延伸阅读14

【参考教材】

Elements of Statistical Learning

Hastie; Tibshirani; Friedman