Class |
Date |
Day |
Topic |
1 |
8/25 |
Thu |
Statistics, Machine Learning,
and Data Mining |
2 |
8/30 |
Tue |
Decision Trees: Recursive Partitioning,
Splitting Rule |
3 |
9/01 |
Thu |
Decision Trees: Efficiency, Pruning,
Converting Trees to Rules |
4 |
9/06 |
Tue |
Train/Test Set Splits |
5 |
9/08 |
Thu |
Artificial Neural Nets: Backpropagation |
6 |
9/13 |
Tue |
Artificial Neural Nets: Overfitting
(Weight Decay, Early Stopping, and Network Size) |
7 |
9/15 |
Thu |
Artificial Neural Nets: Multitask
Learning |
8 |
9/20 |
Tue |
Cross Validation |
9 |
9/22 |
Thu |
Feature Selection |
10 |
9/27 |
Tue |
Data Preprocessing: Attribute
Transformation & Missing Values |
11 |
9/29 |
Thu |
K-Nearest Neighbor |
12 |
10/04 |
Tue |
Boosting & Bagging and the
Bias/Variance Tradeoff |
13 |
10/06 |
Thu |
Boosting & Bagging |
--- |
10/11 |
Tue |
No Class -- Fall Break |
14 |
10/13 |
Thu |
SVMs |
15 |
10/18 |
Tue |
SVMs |
16 |
10/20 |
Thu |
Performance Metrics: Accuracy,
ROC, RMSE, ... |
17 |
10/25 |
Tue |
Empirical Comparison of Learning
Methods |
18 |
10/27 |
Thu |
|
19 |
11/01 |
Tue |
Data Mining of Association Rules |
20 |
11/03 |
Thu |
Agglomerative Clustering |
21 |
11/08 |
Tue |
K-Means Clustering & EM (Expectation
Maximization) |
22 |
11/10 |
Thu |
Scaling Clustering to Large Data
Sets |
23 |
11/15 |
Tue |
Fractal Dimension |
24 |
11/17 |
Thu |
Multi-dimensional Scaling |
25 |
11/22 |
Tue |
|
--- |
11/24 |
Thu |
No Class -- Thanksgiving |
26 |
11/29 |
Tue |
Case Study: Pneumonia Risk Prediction
(Prospective Analysis) |
27 |
12/01 |
Thu |
Case Study: Protein Folding (Clustering,
Visualization, & Discovery) |
--- |
12/09 |
Thu |
Final Exam
(open book) 9:00am-11:30am Place: TBA |