Approximate CS578 Syllabus

Class Date Day Topic
1 8/29 Thu Statistics, Machine Learning, and Data Mining
2 9/03 Tue Decision Trees: Recursive Partitioning, Splitting Rule
3 9/05 Thu Decision Trees: Efficiency, Pruning, Converting Trees to Rules
4 9/10 Tue Train/Test Set Splits
5 9/12 Thu Artificial Neural Nets: Backpropagation
6 9/17 Tue Artificial Neural Nets: Overfitting (Weight Decay, Early Stopping, and Network Size)
7 9/19 Thu Artificial Neural Nets: Multitask Learning
8 9/24 Tue Cross Validation
9 9/26 Thu Feature Selection
10 10/01 Tue Data Preprocessing: Attribute Transformation & Missing Values
11 10/03 Thu K-Nearest Neighbor
12 10/08 Tue Boosting & Bagging
13 10/10 Thu Boosting & Bagging
--- 10/15 Tue No Class -- Fall Break
14 10/17 Thu Data Mining of Association Rules
15 10/22 Tue
16 10/24 Thu
17 10/29 Tue
18 10/31 Thu
19 11/05 Tue
20 11/07 Thu Agglomerative Clustering
21 11/12 Tue K-Means Clustering & EM (Expectation Maximization)
22 11/14 Thu Scaling Clustering to Large Data Sets
23 11/19 Tue Fractal Dimension
24 11/21 Thu Multi-dimensional Scaling
25 11/26 Tue
--- 11/28 Thu No Class -- Thanksgiving
26 12/03 Tue Case Study: Pneumonia Risk Prediction (Prospective Analysis)
27 12/05 Thu Case Study: Protein Folding (Clustering, Visualization, & Discovery)
--- 12/?? ??? Final Exam (open book)