See: Description
| Interface | Description | 
|---|---|
| LeastSquaresOptimizer | An algorithm that can be applied to a non-linear least squares problem. | 
| LeastSquaresOptimizer.Optimum | The optimum found by the optimizer. | 
| LeastSquaresProblem | The data necessary to define a non-linear least squares problem. | 
| LeastSquaresProblem.Evaluation | An evaluation of a  LeastSquaresProblemat a particular point. | 
| MultivariateJacobianFunction | A interface for functions that compute a vector of values and can compute their
 derivatives (Jacobian). | 
| ParameterValidator | Interface for validating a set of model parameters. | 
| ValueAndJacobianFunction | A interface for functions that compute a vector of values and can compute their
 derivatives (Jacobian). | 
| Class | Description | 
|---|---|
| AbstractEvaluation | An implementation of  LeastSquaresProblem.Evaluationthat is designed for extension. | 
| EvaluationRmsChecker | Check if an optimization has converged based on the change in computed RMS. | 
| GaussNewtonOptimizer | Gauss-Newton least-squares solver. | 
| LeastSquaresAdapter | An adapter that delegates to another implementation of  LeastSquaresProblem. | 
| LeastSquaresBuilder | A mutable builder for  LeastSquaresProblems. | 
| LeastSquaresFactory | A Factory for creating  LeastSquaresProblems. | 
| LevenbergMarquardtOptimizer | This class solves a least-squares problem using the Levenberg-Marquardt
 algorithm. | 
| Enum | Description | 
|---|---|
| GaussNewtonOptimizer.Decomposition | The decomposition algorithm to use to solve the normal equations. | 
least-squares optimizers minimize the distance (called
 cost or χ2) between model and
 observations.
 LeastSquaresProblem).
 Such a model predicts a set of values which the algorithm tries to match
 with a set of given set of observed values.
 builder or it can
 be created at once using a factory.Copyright © 2003–2016 The Apache Software Foundation. All rights reserved.