KnnRegressor constructor

KnnRegressor(DataFrame fittingData, String targetName, int k, { KernelType kernel = KernelType.gaussian, Distance distance = Distance.euclidean, DType dtype = dTypeDefaultValue, })

Parameters:

fittingData Labelled observations, among which will be searched k nearest to the given unlabelled observations neighbours. Must contain targetName column.

targetName A string, that serves as a name of the column, that contains labels (or outcomes).

k a number of nearest neighbours to be found among fittingData

kernel a type of a kernel function, that will be used to predict an outcome for a new observation

distance a distance type, that will be used to measure a distance between two observation vectors

dtype A data type for all the numeric values, used by the algorithm. Can affect performance or accuracy of the computations. Default value is dTypeDefaultValue

Implementation

factory KnnRegressor(
  DataFrame fittingData,
  String targetName,
  int k, {
  KernelType kernel = KernelType.gaussian,
  Distance distance = Distance.euclidean,
  DType dtype = dTypeDefaultValue,
}) =>
    initKnnRegressorModule().get<KnnRegressorFactory>().create(
          fittingData,
          targetName,
          k,
          kernel,
          distance,
          dtype,
        );