No class
- Course Logistics
- Guess My Age
- For next time:
- Sign up for slack group
- Set up github account
- Read p. 1 - 14
- Github portfolios
- Estimating f
- For next time:
- Read p 15 - 41
- Problem Set 1 due beginning of next class
- Decomposing MSE
- Bias - Variance Tradeoff
- If time: start Lab 1
- For next time:
- Read p 59 - 81
- Lab 1 due by start of next class
- k-nearest neighbors (KNN)
- Linear Regression
- For next time:
- Read p 82 - 92
- Lab 2 due at beginning of class next Monday
- Extending the linear model
- For next time:
- Read p 92 - 109
- Finish Lab 2
- Review MSE for KNN (from Lab 2)
- Geometry of MLR (housing prices activity)
- Assesssing Model Fit
- For next time:
- Work on Lab 3
- Diagnostics
- Model Validity
- Outliers
- Transformations
- Multicollinearity
- For next time:
- Lab 3 due Friday at noon
- Regression Competition Results
- Automated Model Selection
- For next time:
- Revise
lab-03.Rmdaccording to Activity at end of slides - Read p. 203 - 227
- Revise
- Penalized Regression
- Ridge
- Lasso
- For next time:
- Lab 4
- Classification
- KNN
- Logistic Regression
- For next time:
- Read p. 127 - 149
- Discriminant Analysis
- For next time:
- Lab 5 due Wednesday
- Read p. 149 - 154
- Classification Errors
- Extending Discriminant Analysis
- For next time:
- Lab 5 due
- Study!
- Midterm I
- Resampling
- Validation sets
- Leave-one-out CV
- k-fold CV
- For next time:
- Read p. 175-197
- Bootstrap
- Regression Trees
- For next time:
- Read p. 303-321
- Classification Trees
- For next time:
- Read p. 321-324
- Group Proposals due 11:59 pm Thursday
- Collaborating with GitHub
- Empowering the Tree
- Bagging
- Variable Importance
- Random Forests
- For next time:
- Read p. 321-324
- Write out answers to reading questions for Breiman (see slides)
- Empowering the Tree
- Boosting (by hand)
- Discussion of "Two Cultures"