Approximate CS578 Syllabus

Class Date Day Topic
1 8/28 Thu Statistics, Machine Learning, and Data Mining
2 9/02 Tue Decision Trees: Recursive Partitioning, Splitting Rule
3 9/04 Thu Decision Trees: Efficiency, Pruning, Converting Trees to Rules
4 9/09 Tue Train/Test Set Splits
5 9/11 Thu Artificial Neural Nets: Backpropagation
6 9/16 Tue Artificial Neural Nets: Overfitting (Weight Decay, Early Stopping, and Network Size)
7 9/18 Thu Artificial Neural Nets: Multitask Learning
8 9/23 Tue Cross Validation
9 9/25 Thu Feature Selection
10 9/30 Tue Data Preprocessing: Attribute Transformation & Missing Values
11 10/02 Thu K-Nearest Neighbor
12 10/07 Tue Boosting & Bagging
13 10/09 Thu Boosting & Bagging
--- 10/14 Tue No Class -- Fall Break
14 10/16 Thu Data Mining of Association Rules
15 10/21 Tue
16 10/23 Thu
17 10/28 Tue
18 10/30 Thu
19 11/04 Tue
20 11/06 Thu Agglomerative Clustering
21 11/11 Tue K-Means Clustering & EM (Expectation Maximization)
22 11/13 Thu Scaling Clustering to Large Data Sets
23 11/18 Tue Fractal Dimension
24 11/20 Thu Multi-dimensional Scaling
25 11/25 Tue
--- 11/27 Thu No Class -- Thanksgiving
26 12/02 Tue Case Study: Pneumonia Risk Prediction (Prospective Analysis)
27 12/04 Thu Case Study: Protein Folding (Clustering, Visualization, & Discovery)
--- 12/18 Thu Final Exam (open book)    Place: TBA