New approach to determine the optimal number of clusters K in unsupervised classification.
Oussama ChabihSara SbaiHicham BehjaMohammed Reda Chbihi LouhdiEl Moukhtar ZemmouriBrigitte TroussePublished in: CIST (2021)
Keyphrases
- unsupervised classification
- determine the optimal number
- data clustering
- clustering ensemble
- clustering algorithm
- unsupervised learning
- supervised classification
- cluster analysis
- hierarchical clustering
- remote sensing data
- data points
- consensus clustering
- data sets
- k means
- fuzzy clustering
- hyperspectral images
- self organizing maps
- hyperspectral
- clustering method
- image data
- object recognition
- feature extraction
- feature selection
- learning algorithm
- machine learning