Empirical evaluation of five algorithms for the initialization phase of the k-Means algorithm.
Maria do Carmo NicolettiAnderson Francisco de OliveiraPublished in: Int. J. Hybrid Intell. Syst. (2020)
Keyphrases
- k means
- empirical evaluation
- learning algorithm
- single pass
- significant improvement
- preprocessing phase
- computational cost
- classification algorithm
- related algorithms
- data clustering
- computational efficiency
- theoretical analysis
- benchmark problems
- expectation maximization
- worst case
- computational complexity
- times faster
- optimal solution
- np hard
- computationally efficient
- algorithms require
- image processing algorithms
- preprocessing
- iterative algorithms
- synthetic and real datasets
- center based clustering
- clustering algorithm
- solution quality
- filtering algorithm
- rough k means
- incremental algorithms
- maximum flow
- hybrid algorithm
- search space
- convergence rate
- combinatorial optimization
- optimization algorithm
- dynamic programming
- cost function
- hierarchical clustering
- empirical analyses
- cluster analysis
- optimization problems
- data structure
- fuzzy k means
- multi objective
- clustering approaches
- spectral clustering
- clustering quality
- synthetic datasets
- space complexity