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scalation/scalation/scalation.optimization/scalation.optimization.quasi_newton/LBFGS

LBFGS

scalation.optimization.quasi_newton.LBFGS
See theLBFGS companion object
case class LBFGS(f: FunctionV2S, g: FunctionV2V = ...) extends Minimize

The LBFGS the class implements the Limited-Memory Broyden–Fletcher–Goldfarb–Shanno (BFGS) Quasi-Newton Algorithm for solving Non-Linear Programming (NLP) problems. minimize f(x)

Value parameters

f

the multi-variate objective function to be minimized

gr

its gradient vector-valued function

Attributes

Companion
object
Graph
Supertypes
trait Serializable
trait Product
trait Equals
trait Minimize
class Object
trait Matchable
class Any
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Members list

Value members

Concrete methods

def solve(x0: VectorD, α: Double = ...): FuncVec

Solve the Non-Linear Programming (NLP) problem by starting at x0 and iteratively moving down in the search space to a minimal point. Return the optimal point/vector x and its objective function value. For more options @see LBFGS.lbfgsMain

Solve the Non-Linear Programming (NLP) problem by starting at x0 and iteratively moving down in the search space to a minimal point. Return the optimal point/vector x and its objective function value. For more options @see LBFGS.lbfgsMain

Value parameters

x0

the starting point (initial guess)

α

the current learning rate/step size

Attributes

Inherited methods

def productElementNames: Iterator[String]

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
def productIterator: Iterator[Any]

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
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