LBFGS_B2

scalation.optimization.quasi_newton.LBFGS_B2
See theLBFGS_B2 companion class
object LBFGS_B2

The LBFGS_B2 companion object provides a factory method for Limited memory Broyden–Fletcher–Goldfarb–Shanno for Bounds constrained optimization.

Attributes

Companion
class
Graph
Supertypes
class Object
trait Matchable
class Any
Self type
LBFGS_B2.type

Members list

Value members

Concrete methods

def apply(f: FunctionV2S, n: Int, exactLS: Boolean = ..., l_u_: Bounds = ..., gradF: FunctionV2V = ...): LBFGS_B2

Create an LBFGS_B2 object with a given dimensionality and default lower and upper bounds of -1 and 1, respectively.

Create an LBFGS_B2 object with a given dimensionality and default lower and upper bounds of -1 and 1, respectively.

Value parameters

exactLS

whether to use exact (e.g., GoldenLS) or inexact (e.g., WolfeLS) Line Search

f

the objective function to be minimized

gradF

vector to vector functional formula for computing the gradiant, if available

l_u

(vector, vector) of lower and upper bounds for all input parameters

n

the dimensionality of the search space

Attributes

inline def makeBounds(n: Int, lo: Double, up: Double): Bounds

Make simple bounds where the limits in each dimension is the same.

Make simple bounds where the limits in each dimension is the same.

Value parameters

lo

scalar lower bounds for all input parameters

n

the dimensionality of the search space

up

scalar upper bounds for all input parameters

Attributes

Concrete fields