Sciweavers

Share
ICML
2007
IEEE

Revisiting probabilistic models for clustering with pair-wise constraints

9 years 12 months ago
Revisiting probabilistic models for clustering with pair-wise constraints
We revisit recently proposed algorithms for probabilistic clustering with pair-wise constraints between data points. We evaluate and compare existing techniques in terms of robustness to misspecified constraints. We show that the technique that strictly enforces the given constraints, namely the chunklet model, produces poor results even under a small number of misspecified constraints. We further show that methods that penalize constraint violation are more robust to misspecified constraints but have undesirable local behaviors. Based on this evaluation, we propose a new learning technique, extending the chunklet model to allow soft constraints represented by an intuitive measure of confidence in the constraint.
Blaine Nelson, Ira Cohen
Added 17 Nov 2009
Updated 17 Nov 2009
Type Conference
Year 2007
Where ICML
Authors Blaine Nelson, Ira Cohen
Comments (0)
books