1. “D ATA M INING ON A M USHROOM D ATABASE ” Clara Eusebi, Cosmin Gilga, Deepa John, Andre Maisonave

2. P RESENTATION S UMMARY Background Concepts Literature Review Focus of Study Research Methodology Results of Study Mushroom Database Application Future Research Conclusions

3. B ACKGROUND Algorithms and Techniques Jeff Schlimmer’s Dissertation Confusion Matrix ab 5000a = e [edible] 5495b = p [poisonous]

4. L ITERATURE R EVIEW Overview of Data Mining Decision Trees Visual Classification and Human-Machine Interaction

5. F OCUS OF THE S TUDY Run algorithms in Weka on the Mushroom Database Mushroom Database Application Edible or Poisonous?

6. R ESEARCH M ETHODOLOGY Unpruned decision tree Classifiers that do not generate rules A classifier that does generate rules Jeff Schlimmer’s optimal rule set

7. R ESULTS OF THE S TUDY Results on client databases much higher accuracy Results on Schlimmer’s database Elaborate unpruned tree

8. M USHROOM D ATABASE A PPLICATION Available at: http://utopia.csis.pace.edu/cs691/ 2007- 2008/team6/Mushroom_Database_Application.html

9. F UTURE R ESEARCH Differences between Dr. Cha’s data and Schlimmer’s data

10. C ONCLUSIONS J48 Unpruned Tree Highest accuracy results Mushroom Database Application Human-Machine Interaction