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object SphereGNG

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  1. final case class Config(pd: PD = PD.Uniform, epsilon: Double = 0.02, epsilon2: Double = 0.01, beta: Double = 0.001, alpha: Double = 0.001, lambda: Double = 1.0/100, utility: Double = 4.0, seed: Long = 0L, maxNodes0: Int = 1000, maxEdges0: Int = 6000, maxEdgeAge: Int = 80, maxNeighbors: Int = 10, observer: Observer = Observer.Dummy) extends Product with Serializable

    Configuration of the algorithm.

    Configuration of the algorithm.

    pd

    probability distribution function

    epsilon

    adaptation factor for 'winner' (factor of moving winner node towards pd-emitted position)

    epsilon2

    adaptation factor for neighbours of 'winner' (factor of moving neighbour nodes towards pd-emitted position)

    beta

    controls decay of errors and utilities (decay is 1.0 - beta)

    alpha

    controls decay of errors and utilities for winning nodes (when inserting a new node between them; decay is 1.0 - alpha)

    lambda

    probability of inserting a node (each step)

    utility

    scaling factor such that a node is deleted when utility * node-utility < max-error

    seed

    random number generator initial seed value

    maxNodes0

    initial maximum number of nodes. note that when changing maxNodes later, the values are always clipped to maxNodes0 (there will never be more than maxNodes0 nodes).

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  4. def apply(config: Config): SphereGNG
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  21. object Config extends Serializable

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