知能システム科学専攻 廣田研究室 Guilherme Novaes RAMOS 04M35692

1. Ant Colony Optimization for Hyperbox Clustering and its Application to HPV Virus Classificationハイパーボックス・クラスタリングのためのアント・コロニ最適化とHPVウィルス判別への応用 知能システム科学専攻　廣田研究室 Guilherme Novaes RAMOS 04M35692

2. Motivation • Pattern recognition • Text • Speech • Image • Customer profile • Chemical compounds • Microarrays • …

3. Early diagnosis Human PapillomaVirus • Cervical HPVs • Oral HPVs • Research is not very advanced • Proper treatment • Local risk profile Cancer HPV symptom HPV virus

4. Hyperbox Proposal

5. 1/3 Background:Ant Colony Optimization • Dorigo [IEEE, 97] • Characteristics • Versatile • Robust • Population based

6. 3 2/3 Background:Hyperboxes • Simpson [91] • Defines a region in an n-dimensional space • Described by 2 vectors • Simplest classifier If x  H1Then x Class 1

7. 3/3 Background:Existing applications • ACO • Cemetery approach • Partition matrix • Hyperbox • Min-max fuzzy neural networks • Pattern classification • Clustering • Classifiers

8. Hyperbox clustering with Ant Colony Optimization • Ants scatter hyperboxes in the feature space • Objective: maximize hyperbox density

9. 1/6 Start Stop HACO Initialization Load data Build solution Define C Local optimization Initialize pheromone Update pheromone N Criteria? Y Define Clusters

10. 2/6 Start Stop Criteria? HACO Initialization Build solution Probability Local optimization Exploration Exploitation Assign hyperbox Update pheromone N Y Define Clusters

11. 3/6 Stop Start Criteria? HACO Initialization • Hyperbox density Probability Build solution Generate neighbor Local optimization Update pheromone N Density? Y N Change solution Y Define Clusters

12. 4/6 Start Stop Criteria? HACO Initialization • ij : pheromone value • : trail persistance • best: hyperbox density of best solution Build solution Local optimization Update pheromone N Y Define Clusters

13. HACO 5/6 Start Stop ACO Criteria? HACO Initialization • Fitness (density) • Number of iterations • Comparison with previous solutions • … Build solution Local optimization Update pheromone N Density Fitness Y Define Clusters Iteration

14. 6/6 Start Stop Criteria? HACO Initialization • Overlapping • Nearest neighbor Build solution Local optimization Update pheromone N Y Define Clusters

15. Experiments • Specifications • Pentium M 1.6GHz, 512 MB of RAM • C++ • Suse Linux • Data sets • 3 computer generated • HPV

16. 1/6 Experiments - Dataset 1 ACO HACO NN FCM 150 samples, 2 dimensions

17. 2/6 Experiments - Dataset 2 ACO HACO NN FCM 302 samples, 2 dimensions

18. 3/6 Experiments - Dataset 3 ACO HACO NN FCM 600 samples, 2 dimensions

19. 4/6 Experiments - Results

20. 5/6 Experiments - HPV Data • Department of stomatology • Dentistry School • Characteristics • 199 samples • 42 attributes

21. 6/6 Experiments - Results

22. Conclusions • Pattern recognition • Probable HPV risk profile • Advantages • Higher accuracy • Competitive runtime • ACO(HPV) • 29.1% - 36.3% more accurate • 82.6% - 97.6% faster

23. Perspectives • Test with larger data sets • Automatic parameter setting • Hyperbox shape optimization • Compare/Apply other tools • GA • SOM • …

24. Thank you for your attention

25. HPV statistics • Over 100 viruses • 500,000 new cases of cancer diagnosed each year • 200,000 deaths each year

26. Parameters

27. 1/6 Hyperbox Number •  : search space ratio • n : attributes • Dk : k-th dimension length • xk:k-th attribute of samples