ml-levenberg-marquardt
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    Interface LevenbergMarquardtOptions

    interface LevenbergMarquardtOptions {
        centralDifference?: boolean;
        damping?: number;
        dampingStepDown?: number;
        dampingStepUp?: number;
        errorTolerance?: number;
        gradientDifference?: number | ArrayLike<number>;
        improvementThreshold?: number;
        initialValues: ArrayLike<number>;
        maxIterations?: number;
        maxValues?: ArrayLike<number>;
        minValues?: ArrayLike<number>;
        timeout?: number;
        weights?: number | ArrayLike<number>;
    }
    Index

    Properties

    centralDifference?: boolean

    If true the jacobian matrix is approximated by central differences otherwise by forward differences

    false
    
    damping?: number

    Levenberg-Marquardt parameter, small values of the damping parameter λ result in a Gauss-Newton update and large values of λ result in a gradient descent update

    1e-2
    
    dampingStepDown?: number

    factor to reduce the damping (Levenberg-Marquardt parameter) when there is not an improvement when updating parameters.

    9
    
    dampingStepUp?: number

    factor to increase the damping (Levenberg-Marquardt parameter) when there is an improvement when updating parameters.

    11
    
    errorTolerance?: number

    Minimum uncertainty allowed for each point.

    10e-3
    
    gradientDifference?: number | ArrayLike<number>

    The step size to approximate the jacobian matrix

    10e-2
    
    improvementThreshold?: number

    the threshold to define an improvement through an update of parameters

    1e-3
    
    initialValues: ArrayLike<number>

    Array of initial parameter values

    maxIterations?: number

    Maximum of allowed iterations

    100
    
    maxValues?: ArrayLike<number>

    Maximum allowed values for parameters

    minValues?: ArrayLike<number>

    Minimum allowed values for parameters

    timeout?: number

    maximum time running before throw in seconds.

    weights?: number | ArrayLike<number>

    weighting vector, if the length does not match with the number of data points, the vector is reconstructed with first value.

    1