ml-spectra-processing
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    Interface CalculateAdaptiveWeightsOptions

    interface CalculateAdaptiveWeightsOptions {
        controlPoints?: NumberArray;
        factorStd?: number;
        learningRate?: number;
        minWeight?: number;
        weights?: NumberArray;
    }

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    Properties

    controlPoints? factorStd? learningRate? minWeight? weights?

    Properties

    controlPoints?: NumberArray

    Control points to determine which weights to update.

    factorStd?: number

    Factor used to calculate the threshold for determining outliers in the residuals. Higher values mean more tolerance for outliers. The default value is based on noise follow the normal distribution values over 3 times the standard-deviation could be marked as signals or outliers.

    3
    learningRate?: number

    Factor that determines how quickly the weights are updated in each iteration. A value between 0 and 1, where higher values mean faster updates.

    0.5
    minWeight?: number

    The minimum allowed weight value to prevent weights from becoming too small.

    0.01
    weights?: NumberArray

    Array of weights

    [1,1,...,1]

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