| Date | Topic | |
|---|---|---|
| 8/27 | Introduction | |
| One dimensional data | ||
| 8/29 | Viewing and summarizing Stripcharts, boxplots, transformation |
|
| 8/31 |
Using probabilistic models Classification and anomaly detection using histograms |
|
| 9/5,7,10 |
Abstraction hierarchies Choosing abstraction levels Details of classification and abstraction Category merging and the balance principle |
|
| 9/12,14 |
Density-preserving abstraction More on density-preserving abstraction Histograms with confidence intervals, bin merging |
|
| 9/17,19,21 |
Numerical abstraction by clustering sum-of-squares criterion, Ward's method, k-means Applying abstraction More applications Museum visitor profiling, color tracking, change-point analysis |
|
| Contingency tables | ||
| 9/24 |
Visualizing contingency tables Mosaic plots |
|
| 9/26 |
Sorting contingency tables Correspondence analysis |
|
| 9/28 |
Measuring deviations from independence Lift and its confidence interval |
|
| 10/1 |
Association mining Market basket analysis, support/confidence |
|
| 10/3,10/5 |
Predictive abstraction Applying predictive abstraction Mining abstract association rules, merging rows/columns of a contingency table |
|
| Prediction using trees | ||
| 10/8 | Merging numerical batches Properties of lift, log-variance merging criterion |
|
| 10/10,12 | Regression trees Regression tree residuals |
|
| 10/15 | Classification trees | |
| 10/17,24,26 |
Performance assessment Examples of performance assessment Classification uncertainty |
|
| Prediction using additive and multiplicative models | ||
| 10/29,31 11/2 |
Response tables Using additive models Bilinear extension two-way ANOVA, profile plots |
|
| Scatterplots and regression | ||
| 11/5,7,9 | Linear regression Multiple regression Multiple regression with interactions |
|
| Classification | ||
| 11/12,14 | Logistic regression Applying logistic regression |
|
| 11/16,19 | Nearest-neighbor classification Distances and transformations |
|
| Visualizing high dimensional data | ||
| 11/26,28 | Multivariate geometry Projection examples Grand tour, principal components analysis, discriminative projection |
|
| 11/30 | Multivariate clustering Ward's method, single-link |
|
| 12/3 | Multivariate profiles Star plot, parallel-coordinate plot |
|
| 12/5 | Multivariate outliers | |
| 12/7,10 | Course overview More course overview |