SEDS 535
Knowledge Discovery
Knowledge discovery and data mining, data warehousing, data preparation and data mining primitives, concept description, mining association rules in large databases, classification and prediction, cluster analysis, web mining, applications in data mining.
| Week | Topics |
|---|---|
| 1 | Introduction |
| 2 | Measurement and Data, Visualizing and Exploring Data |
| 3 | A Systematic Overview of Data Mining Algorithms |
| 4 | Models and Patterns |
| 5 | Score Functions for Data Mining Algorithms |
| 6 | Dimensionality Reduction |
| 7 | Descriptive Modeling I |
| 8 | Search and Optimization Methods |
| 9 | Descriptive Modeling II |
| 10 | Predictive Modeling for Classification I |
| 11 | Predictive Modeling for Classification II |
| 12 | Association Analysis I |
| 13 | Association Analysis II |
| 14 | Link Analysis |
