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lazy (version 1.2-14)

lazy.control: Set parameters for lazy learning

Description

Set control parameters for a lazy learning object.

Usage

lazy.control(conIdPar=NULL, linIdPar=1, quaIdPar=NULL,
                distance=c("manhattan","euclidean"), metric=NULL,
                   cmbPar=1, lambda=1e+06)

Arguments

conIdPar
Parameter controlling the number of neighbors to be used for identifying and validating constant models. conIdPar can assume different forms: [object Object],[object Object],[object Object],[object Object]
linIdPar
Parameter controlling the number of neighbors to be used for identifying and validating linear models. linIdPar can assume different forms: [object Object],[object Object],[object Object],[object Object]
quaIdPar
Parameter controlling the number of neighbors to be used for identifying and validating quadratic models. quaIdPar can assume different forms: [object Object],[object Object],[object Object],[object Object]
distance
The distance metric: can be manhattan or euclidean.
metric
Vector of n elements. Weights used to evaluate the distance between query point and neighbors.
cmbPar
Parameter controlling the local combination of models. cmbPar can assume different forms: [object Object],[object Object]
lambda
Initialization of the diagonal elements of the local variance/covariance matrix for Ridge Regression.

Value

  • The output of lazy.control is a list containing the following components: conIdPar, linIdPar, quaIdPar, distance, metric, cmbPar, lambda.

See Also

lazy, predict.lazy