Project Details
Description
This Phd try to develop new dissimilarities measures for hierarchical
agglomerative clustering. These new dissimilarities measures are based
on non parametric density estimations and
empirical distributions. The development of these new methods is
complementary and dual to clustering trees methods explained in J.-Y.
Pirçon's Phd (2004).
agglomerative clustering. These new dissimilarities measures are based
on non parametric density estimations and
empirical distributions. The development of these new methods is
complementary and dual to clustering trees methods explained in J.-Y.
Pirçon's Phd (2004).
Status | Finished |
---|---|
Effective start/end date | 1/09/04 → 31/08/08 |
Keywords
- empirical distribution
- dissimilarity
- density estimation
- Hierarchical agglomerative clustering
Fingerprint
Explore the research topics touched on by this project. These labels are generated based on the underlying awards/grants. Together they form a unique fingerprint.