A Lagrangian-based approach to learn distance metrics for clustering with minimal data transformation.
Rodrigo RandelDaniel AloiseAlain HertzPublished in: SDM (2023)
Keyphrases
- distance metric
- data transformation
- distance metric learning
- distance function
- euclidean distance
- metric learning
- data integration
- data points
- distance measure
- privacy preserving
- functional dependencies
- data mining
- data quality
- privacy preserving data mining
- data warehousing
- dimensionality reduction
- clustering algorithm
- clustering method
- document clustering
- data privacy
- pairwise constraints
- data sets