Enhanced Clinical Interpretability of Feature Selection via Latent Component-based Variable Clustering.
Hu T. HuangFoad GreenRayna MatsunoJoshua LovingPublished in: AMIA (2022)
Keyphrases
- feature selection
- clustering algorithm
- clustering method
- k means
- document clustering
- unsupervised learning
- high dimensionality
- categorical data
- text categorization
- feature set
- mutual information
- unsupervised feature selection
- data pre processing
- cluster analysis
- machine learning
- classification accuracy
- hierarchical clustering
- spectral clustering
- feature weighting
- clinical data
- data mining and pattern recognition
- clinical practice
- medical data
- multi task
- fuzzy clustering
- latent variables
- support vector machine
- information theoretic
- self organizing maps