Trait

io.github.mandar2812.dynaml.optimization

Optimizer

Related Doc: package optimization

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trait Optimizer[P, Q, R, S] extends Serializable

Trait for optimization problem solvers.

P

The type of the parameters of the model to be optimized.

Q

The type of the predictor variable

R

The type of the target variable

S

The type of the edge containing the features and label.

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Serializable, Serializable, AnyRef, Any
Known Subclasses
BackPropagation, CommitteeModelSolver, ConjugateGradient, ConjugateGradientSpark, FFBackProp, GradBasedBackPropagation, GradientDescent, GradientDescentSpark, LSSVMLinearSolver, LaplacePosteriorMode, QuasiNewtonOptimizer, RDDCommitteeSolver, RegularizedLSSolver, RegularizedOptimizer
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Abstract Value Members

  1. abstract def optimize(nPoints: Long, ParamOutEdges: S, initialP: P): P

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    Solve the convex optimization problem.

Concrete Value Members

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

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  2. final def ##(): Int

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  4. final def asInstanceOf[T0]: T0

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  5. def clone(): AnyRef

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

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  7. def equals(arg0: Any): Boolean

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  8. def finalize(): Unit

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

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  10. def hashCode(): Int

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  11. final def isInstanceOf[T0]: Boolean

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

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  13. final def notify(): Unit

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  14. final def notifyAll(): Unit

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

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  17. final def wait(): Unit

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

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

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