Relevance of Course Objectives and Core Learning Outcomes(%) |
Teaching and Assessment Methods for Course Objectives |
Course Objectives |
Competency Indicators |
Ratio(%) |
Teaching Methods |
Assessment Methods |
To understand the statistical learning methods and acquire the skills of data analysis using R. |
1.Mathematical Thinking and Logic |
7.Literature Review |
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Oral Presentation |
Attendance |
Assignment |
Written Presentation |
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Course Content and Homework/Schedule/Tests Schedule |
Week |
Course Content |
Week 1 |
Using R language |
Week 2 |
Using R language |
Week 3 |
Multivariate normal distribution |
Week 4 |
Least square (LS) regression |
Week 5 |
Maximum likelihood (ML) regression |
Week 6 |
GCV, AIC: Best subset regression |
Week 7 |
Stepwise regression |
Week 8 |
L2-norm regularized (ridge) regression (RR) |
Week 9 |
Adaptive weighted ridge regression (AWRR) |
Week 10 |
Polynomial regression; Basis function and data transformation |
Week 11 |
Ridge regression with the (spline) basis expansion |
Week 12 |
Additive model (I) with the RR |
Week 13 |
Additive model (II) with the AWRR |
Week 14 |
Smoothing spline (I) |
Week 15 |
Smoothing spline (II) |
Week 16 |
Final reports
Self-learning (Additive model estimated by the backfitting algorithm)
Assignment: homework problems + learning experience report
Self-learning (Additive model estimated by the stagewise regression (boosting))
Assignment: homework problems + learning experience report |
self-directed learning |
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Evaluation |
Class attendance and homework assignments: 45%
Final report: 45%
Self-learning: 10%
The grade system is tentative and subject to modification.
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Textbook & other References |
The elements of statistical learning by Hastie et al.
Distributed optimization and statistical learning via the alternating direction method of multipliers by Boyd et al.
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Teaching Aids & Teacher's Website |
Supplementary web resources
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Office Hours |
2:00-3:00 PM Friday
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Sustainable Development Goals, SDGs(Link URL) |
04.Quality Education | include experience courses:N |
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