An empirical comparison between stochastic and deterministic centroid initialisation for K-means variations.
Avgoustinos VourosStephen LangdellMike CroucherEleni VasilakiPublished in: Mach. Learn. (2021)
Keyphrases
- k means
- stochastic optimization problems
- clustering algorithm
- stochastic methods
- data clustering
- cluster analysis
- clustering method
- monte carlo sampling
- spectral clustering
- self organizing maps
- fuzzy c means
- machine learning
- expectation maximization
- monte carlo
- rough k means
- black box
- random variables
- variable weighting
- information systems
- cluster centers
- fuzzy k means
- stochastic optimization
- view angle
- real time
- stochastic domains
- stochastic nature
- fully observable
- genetic algorithm
- learning algorithm
- objective function
- stochastic process
- stochastic model
- document clustering
- hierarchical clustering
- reinforcement learning