public class GaussNewtonOptimizer extends AbstractLeastSquaresOptimizer
This class solve a least-square problem by solving the normal equations of the linearized problem at each iteration. Either LU decomposition or QR decomposition can be used to solve the normal equations. LU decomposition is faster but QR decomposition is more robust for difficult problems.
evaluations, iterations
Constructor and Description |
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GaussNewtonOptimizer(boolean useLUIn,
ConvergenceChecker<PointVectorValuePair> checker) |
GaussNewtonOptimizer(ConvergenceChecker<PointVectorValuePair> checker)
Simple constructor with default settings.
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Modifier and Type | Method and Description |
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PointVectorValuePair |
doOptimize()
Performs the bulk of the optimization algorithm.
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computeCost, computeCovariances, computeResiduals, computeSigma, computeWeightedJacobian, getChiSquare, getRMS, getWeightSquareRoot, optimize, setCost
computeJacobian
computeObjectiveValue, getTarget, getTargetSize, getWeight
getLowerBound, getStartPoint, getUpperBound
getConvergenceChecker, getEvaluations, getIterations, getMaxEvaluations, getMaxIterations, incrementEvaluationCount, incrementIterationCount
public GaussNewtonOptimizer(ConvergenceChecker<PointVectorValuePair> checker)
checker
- Convergence checker.public GaussNewtonOptimizer(boolean useLUIn, ConvergenceChecker<PointVectorValuePair> checker)
useLUIn
- If true
, the normal equations will be solved
using LU decomposition, otherwise they will be solved using QR
decomposition.checker
- Convergence checker.public PointVectorValuePair doOptimize()
doOptimize
in class BaseOptimizer<PointVectorValuePair>
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