Interface CalculateAdaptiveWeightsOptions

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

Hierarchy (View Summary)

Properties

controlPoints? factorStd? learningRate? minWeight? weights?

Properties

OptionalcontrolPoints

controlPoints?: NumberArray

Control points to determine which weights to update.

OptionalfactorStd

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.

Default

3

OptionallearningRate

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.

Default

0.5

OptionalminWeight

minWeight?: number

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

Default

0.01

Optionalweights

weights?: NumberArray

Array of weights

Default

[1,1,...,1]

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