Aggregation Trees for visualization and dimension reduction in many-objective optimization.
Alan R. R. de FreitasPeter J. FlemingFrederico G. GuimarãesPublished in: Inf. Sci. (2015)
Keyphrases
- k means
- dimension reduction
- cluster analysis
- self organizing maps
- generative topographic mapping
- principal component analysis
- data clustering
- manifold learning
- feature extraction
- high dimensional problems
- data mining and machine learning
- multiple objectives
- partial least squares
- low dimensional
- variable selection
- singular value decomposition
- unsupervised learning
- decision trees
- random projections
- high dimensional
- feature selection
- expectation maximization
- high dimensional data
- feature space
- dimensionality reduction
- data analysis
- high dimensional data analysis
- high dimensionality
- linear discriminant analysis
- multi objective
- discriminative information
- discriminant analysis
- decomposition method
- reinforcement learning
- machine learning
- manifold embedding
- real world
- database