Preference representation using Gaussian functions on a hyperplane in evolutionary multi-objective optimization.
Kaname NarukawaYu SetoguchiYuki TanigakiMarkus OlhoferBernhard SendhoffHisao IshibuchiPublished in: Soft Comput. (2016)
Keyphrases
- hyperplane
- evolutionary multi objective optimization
- data points
- support vector
- linear classifiers
- feature space
- training samples
- support vector machine
- incremental learning algorithm
- maximal margin
- multi objective
- kernel space
- principal components
- machine learning
- function approximation
- support vectors
- normal vectors
- linearly separable
- classification procedure
- convex hull
- kernel function
- data analysis
- genetic algorithm