Interpretable Bayesian network abstraction for dimension reduction.
Hasna NjahSalma JamoussiWalid MahdiPublished in: Neural Comput. Appl. (2023)
Keyphrases
- dimension reduction
- bayesian networks
- high dimensional
- feature extraction
- principal component analysis
- singular value decomposition
- high dimensional problems
- random projections
- low dimensional
- variable selection
- high dimensional data
- data mining and machine learning
- manifold learning
- partial least squares
- feature space
- linear discriminant analysis
- graphical models
- feature selection
- cluster analysis
- dimensionality reduction
- discriminative information
- probabilistic model
- high dimensionality
- high dimensional data analysis
- unsupervised learning
- dimension reduction methods
- database
- discriminant analysis
- active learning
- object recognition
- pattern recognition
- decision trees
- data sets