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Evolutionary Learning
Explicit Components
Supervised Learning


Calculates the Hypervolume of the ParetoFront of a multi-dimensional set of points; exact algorithm; normalizes the pareto front to objectives between 0 and 1


Octopus SolutionOSThe solutions to calculate the HV forOctopus Solution
Reference Point coordinateRThe point in objective space against which the Hypervolume is calculated, given by only one coordinate which is applied to each objective dimension. The coordinate relates to the normalized pareto-front which is between 0 and 1Number


HVHVThe HypervolumeNumber
pareto BoundsPBThe bounds of the objectives in the pareto-frontDomain
total BoundsTBThe bounds of the objectives in the entire set suppliedDomain
Front SolutionsFthe pareto frontOctopus Solution
non-Front SolutionsNthe solutions not part of the pareto frontOctopus Solution

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