1. An Extension of Table Lens CPSC 533 Information Visualization Course Project, Term 2, 2003 Fengdong Du

2. Table Lens Technique Show a large amount of information in a relatively small table. Preserve Global context Detail-on-demand presentation Support simple pattern discovery

4. Extension of Table Lens Display not only large amount of data but also relatively large dimensionality. Combine data mining techniques to facilitate discovering more complicated pattern.

5. Project Proposal: Combine Table Len with Classification Rule Mining

6. Classification Mining Generate classification rules given a set of training data. Class label is treated as a function of a set of non-class attribute. Find the minimum set of attributes that predict the class attribute with high accuracy.

7. Example PlayTennisOutlookWindyTemp. YesOvercastFalseNormal NoRainingTrueNormal ………… Rule: Outlook=overcastPlayTennis=Yes

8. Combining Table Len with Classification Rule Mining Put class label attribute and class predict as the most interested attribute. Class attribute and class predict are never demagnified.

9. (Continued) All the remaining attributes are demagnified by their “importance” of classing the data. Possibly show a relatively large dimensionality, e.g. less than 50 attributes.

10. (Continued) Attribute details are showed when users move focus to head of that column. Data record details are showed when users move focus to that row.

11. (subject to a lot of change and improvement)