Object

fr.iscpif.mgo

diversity

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object diversity

Layer of the cake that compute a diversity metric for a set of values

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  1. type Diversity[M[_], I] = Kleisli[M, Vector[I], Vector[Lazy[Double]]]

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    Compute the diversity metric of the values

Value Members

  1. final def !=(arg0: Any): Boolean

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  2. final def ##(): Int

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  3. final def ==(arg0: Any): Boolean

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  4. object Diversity

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  5. def KNearestNeighbours[M[_], I](k: Int, fitness: Fitness[I, Seq[Double]])(implicit MM: Monad[M]): Diversity[M, I]

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  6. final def asInstanceOf[T0]: T0

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  7. def clone(): AnyRef

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  8. def crowdingDistance[M[_], I](fitness: Fitness[I, Seq[Double]])(implicit MM: Monad[M], MR: RandomGen[M]): Diversity[M, I]

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  9. final def eq(arg0: AnyRef): Boolean

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  10. def equals(arg0: Any): Boolean

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  11. def finalize(): Unit

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  12. final def getClass(): Class[_]

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  13. def hashCode(): Int

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  14. def hypervolumeContribution[M[_], I](referencePoint: ReferencePoint, fitness: Fitness[I, Seq[Double]])(implicit MM: Monad[M]): Diversity[M, I]

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  15. final def isInstanceOf[T0]: Boolean

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  16. final def ne(arg0: AnyRef): Boolean

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  17. final def notify(): Unit

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  18. final def notifyAll(): Unit

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  19. final def synchronized[T0](arg0: ⇒ T0): T0

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  20. def toString(): String

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  21. final def wait(): Unit

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  22. final def wait(arg0: Long, arg1: Int): Unit

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  23. final def wait(arg0: Long): Unit

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