An algorithm for k-anonymous microaggregation and clustering inspired by the design of distortion-optimized quantizers.
David Rebollo-MonederoJordi FornéMiguel SorianoPublished in: Data Knowl. Eng. (2011)
Keyphrases
- k means
- clustering method
- information loss
- computational complexity
- hierarchical clustering
- dynamic programming
- cost function
- search space
- learning algorithm
- preprocessing
- optimal solution
- expectation maximization
- objective function
- prediction error
- distance metric
- data clustering
- np hard
- data sets
- input data
- information theoretic
- spectral clustering
- similarity measure