clusteringfittingintegrationinterpolationjavaleast-squaresmathoptimizationpolynomialsolverstattransforms
06d490a4bd
The weights are no longer implicit in LeastSquaresProblem.Evaluation. They are already included in the computed residuals and Jacobian. GN and LM multiplied the residuals by the weights immediately, so that was easy to remove. Created an AbstractEvaluation class which handles the derived quantitied (cost, rms, covariance,...) and two implementations. UnweightedEvaluation uses the straight forward formulas. DenseWeightedEvaluation delegates to an Evaluation and multiples the residuals and Jacobian by the square root of the weight matrix before returning them. Allowed me to remove the reference to the full weight matrix. git-svn-id: https://svn.apache.org/repos/asf/commons/proper/math/trunk@1569344 13f79535-47bb-0310-9956-ffa450edef68 |
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