LBFGS

scalation.optimization.quasi_newton.LBFGS
See theLBFGS companion class
object LBFGS extends PathMonitor

The LBFGS object implementats of the Limited memory Broyden–Fletcher–Goldfarb–Shanno (BFGS) for unconstrained optimization (L-BFGS) algorithm. This Scala implementation was made based on the C implementation of the same algorithm found in the following link.

Attributes

See also

github.com/chokkan/liblbfgs

Companion
class
Graph
Supertypes
trait PathMonitor
class Object
trait Matchable
class Any
Self type
LBFGS.type

Members list

Value members

Concrete methods

def lbfgsMain(n: Int, x: VectorD, functionLogic: EvaluationLogic | OptimizationLogic, params: LBFGSPrms, instance: Any): LBFGSResults

Performs the L-BFGS optimization that optimizes variables to minimize a function value.

Performs the L-BFGS optimization that optimizes variables to minimize a function value.

Value parameters

functionLogic

the logic defining the objective function and its gradient

n

the dimensionality of the optimization problem

x

the starting point (initial guess)

Attributes

Inherited methods

def add2Path(x: VectorD): Unit

Adds a new multidimensional point to the path being monitored.

Adds a new multidimensional point to the path being monitored.

Value parameters

x

the data point to be added to the path being monitored.

Attributes

Inherited from:
PathMonitor
def clearPath(): Unit

Clears the current path being monitored.

Clears the current path being monitored.

Attributes

Inherited from:
PathMonitor
def getPath: ArrayBuffer[VectorD]

Returns a deep copy of the data path being monitored.

Returns a deep copy of the data path being monitored.

Attributes

Returns

ArrayBuffern [VectorD], a deep copy of the data path being monitored.

Inherited from:
PathMonitor