scalation.optimization.quasi_newton.FunctionEvaluation
See theFunctionEvaluation companion object
The FunctionEvaluation case class to store the definition of a function evaluation in a format that adheres to the evaluation logic format used by the implementation of the Limited memory Broyden–Fletcher–Goldfarb–Shanno (BFGS) for unconstrained optimization (L-BFGS) algorithm.
Value parameters
gradFunction
the gradient vector-valued function (vector -> vector)
objFunction
the multi-variate objective function (vector -> scalar)
Attributes
Companion
object
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Supertypes
trait Serializable
trait Product
trait Equals
class Object
trait Matchable
class Any
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This constructor uses numerical approximation for the gradient which is less accurate than hard-coded definition of gradient function.
This constructor uses numerical approximation for the gradient which is less accurate than hard-coded definition of gradient function.
Value parameters
objFunction
the object finction to be optimized
Attributes
Evaluates the gradients and objective function according to the state of the variables during the minimization process.
Evaluates the gradients and objective function according to the state of the variables during the minimization process.
Value parameters
instance
an optional user data segment that may be provided when calling the LBFGS.lbfgsMain method (@see OptimizationLogic)
n
the number of variables
step
current step chosen by the line search routine.
x
VectorD with the current values of the variables
Attributes
Returns
LBFGSVarEvaluationResults, results obtained from evaluating the variables
An iterator over the names of all the elements of this product.
An iterator over the names of all the elements of this product.
Attributes
Inherited from:
Product
An iterator over all the elements of this product.
An iterator over all the elements of this product.
Attributes
Returns
in the default implementation, an Iterator[Any]
Inherited from:
Product