Package-level declarations
Functions
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fun kernelShap(background: Array<DoubleArray>, numSamples: Int = 0, ridge: Double = 1.0E-8, predictor: ToDoubleFunction<DoubleArray>): KernelSHAP<DoubleArray>
Creates a KernelSHAP explainer for a scalar function on DoubleArray.
fun kernelShap(background: Array<DoubleArray>, model: Classifier<DoubleArray>, numSamples: Int = 0, ridge: Double = 1.0E-8): KernelSHAP<DoubleArray>
Creates a KernelSHAP explainer for a Classifier model on DoubleArray.
fun kernelShap(background: Array<DoubleArray>, model: Regression<DoubleArray>, numSamples: Int = 0, ridge: Double = 1.0E-8): KernelSHAP<DoubleArray>
Creates a KernelSHAP explainer for a Regression model on DoubleArray.
fun kernelShap(background: DataFrame, model: DataFrameClassifier, numSamples: Int = 0, ridge: Double = 1.0E-8): KernelSHAP<Tuple>
Creates a KernelSHAP explainer for a DataFrameClassifier model.
fun kernelShap(background: DataFrame, model: DataFrameRegression, numSamples: Int = 0, ridge: Double = 1.0E-8): KernelSHAP<Tuple>
Creates a KernelSHAP explainer for a DataFrameRegression model.
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fun kernelShapVector(background: Array<DoubleArray>, numSamples: Int = 0, ridge: Double = 1.0E-8, predictor: Function<DoubleArray, DoubleArray>): KernelSHAP<DoubleArray>
Creates a KernelSHAP explainer for a vector-valued function on DoubleArray.