A comprehensive survey of clustering algorithms: State-of-the-art machine learning applications, taxonomy, challenges, and future research prospects.
Absalom E. EzugwuAbiodun M. IkotunOlaide Nathaniel OyeladeLaith Mohammad AbualigahJeffrey O. AgushakaChristopher I. EkeAndronicus Ayobami AkinyeluPublished in: Eng. Appl. Artif. Intell. (2022)
Keyphrases
- machine learning
- clustering algorithm
- lessons learned
- pattern recognition
- real world
- promising directions
- machine learning algorithms
- learning algorithm
- clustering method
- machine learning methods
- k means
- density based clustering
- semi supervised learning
- fuzzy clustering
- computational intelligence
- text mining
- supervised learning
- inductive learning
- key issues
- machine learning approaches
- computer science
- paradigm shift
- computer vision
- fuzzy c means
- document clustering
- data mining
- cluster analysis
- text classification
- knowledge representation
- long term
- statistical methods
- model selection
- data clustering
- inductive logic programming
- knowledge acquisition
- support vector machine
- graph clustering
- decision trees
- clustering framework
- feature selection
- artificial intelligence
- advanced technologies