transformdata: Transform the data with normalization and/or spline basis

In SVMMaj: Implementation of the SVM-Maj Algorithm

Transform the data with normalization and/or spline basis

Description

Performs subsequently a normalization of the input data and creating spline basis based on the user defined input

Usage

transformdata(x, standardize = c("interval", "zscore", "none"),
  spline.knots = 0, spline.degree = 1)

Arguments

x	a single column of values as input for the data transformation
standardize	Either a string value denoting a predefined scaling, or a list with values a and b corresponding with the numeric centering and scaling, that is, using the function x * standardize$b - standardize$a.
spline.knots	Number of inner knots to use. isb will equally distribute the knots over the value range using quantiles. spline.knots will only be used if knots is not given.
spline.degree	The polynomial degree of the spline basis.

Value

transformed data in spline basis or (in case of no spline) a normalized vector

SVMMaj documentation built on May 23, 2022, 9:05 a.m.