![]() ![]() O Support Vector Machines Instructor: Yufeng Liu ![]() O Logistic regression and penalized logistic regression O Linear regression and penalized regression Participants should be familiar with linear regression and basic statistical and probability concepts, as well as some familiarity with R programming. This course is intended for researchers who have some knowledge of statistics and want to be introduced to statistical machine learning and data mining, or practitioners who would like to apply statistical machine learning techniques to their problems. The techniques discussed will be demonstrated in R. The main emphasis will be on the analysis of real data sets from various scientific fields. Supervised learning techniques will be covered, including penalized regression such as LASSO and its variants, support vector machines. This short course will provide an overview of statistical machine learning and data mining techniques with applications to the analysis of real data. Many statistical machine learning and data mining techniques and algorithms are very useful for various scientific areas. Statistical machine learning and data mining is an interdisciplinary research area which is closely related to statistics, computer sciences, engineering, and bioinformatics. Attendance is required as the course will not be recorded. This two day ( and ) course will be offered via Zoom. ![]()
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