Exploring High-dimensional Rules Indirectly via Latent Space Through a Dimensionality Reduction for XCS.
Naoya YatsuHiroki ShiraishiHiroyuki SatoKeiki TakadamaPublished in: GECCO (2023)
Keyphrases
- dimensionality reduction
- latent space
- high dimensional
- low dimensional
- lower dimensional
- learning classifier systems
- low dimensional spaces
- high dimensional data
- manifold learning
- high dimensionality
- dimension reduction
- feature space
- high dimensional spaces
- principal component analysis
- linear discriminant analysis
- data points
- feature selection
- random projections
- pattern recognition
- gaussian process latent variable models
- parameter space
- euclidean distance
- euclidean space
- nearest neighbor
- feature extraction
- sparse representation
- similarity search
- data mining
- original data
- distance metric
- data sets
- negative matrix factorization
- regression model