Selecting the number of clusters, clustering models, and algorithms. A unifying approach based on the quadratic discriminant score.
Luca CoraggioPietro CorettoPublished in: CoRR (2021)
Keyphrases
- feature set
- data clustering
- feature selection
- clustering algorithm
- hierarchical clustering
- cluster centers
- k means
- clustering quality
- theoretical analysis
- learning models
- synthetic datasets
- agglomerative hierarchical clustering
- probabilistic model
- self organizing maps
- cluster analysis
- homogeneous groups
- clustering approaches
- document clustering
- data points
- validity measures
- overlapping clusters
- validity indices
- intra cluster
- consensus clustering
- graph clustering
- high dimensional
- data mining