XplainableClusterExplorer: a novel approach for interactive feature selection for clustering.
Eric FezerDominik RaabAndreas TheisslerPublished in: VINCI (2020)
Keyphrases
- feature selection
- unsupervised feature selection
- high dimensionality
- k means
- clustering algorithm
- clustering method
- self organizing maps
- text categorization
- unsupervised learning
- feature set
- information theoretic
- machine learning
- mutual information
- spectral clustering
- user friendly
- user interaction
- data clustering
- class separability
- hierarchical clustering
- graph theoretic
- computer graphics
- text classification
- data pre processing
- feature space
- data mining and pattern recognition
- redundant features
- minimum message length
- data sets
- feature selection algorithms
- fuzzy clustering
- document clustering
- cluster analysis
- classification accuracy
- high dimensional
- feature extraction
- data mining