SimData: SimData

In snnR: Sparse Neural Networks for Genomic Selection in Animal Breeding

Description

Function to create simulation data of nonlinear function or nonlinear classification.

Usage

   SimData(type,nsamples,nvaibles,nClasses) 

Arguments

type	If type="Nonlinearregress", this function creates simulation data of nonlinear function. If type="Nonlinearregress", this function creates simulation data of nonlinear classification.
nsamples	positive integer, the samples size of data.
nvaibles	positive integer, the vaible size of data.
nClasses	positive integer, the number of classes for nonlinear classification.

Value

A vector of simulation data of nonlinear function or nonlinear classification .

Examples

## Not run: 
###############################################################
#Example 1
 nsamples = 200
 nvaibles = 1
 # Simulation data of nonlinear function with 200 samples and 1 varible input.
 NonlinregressData=SimData("Nonlinearregress",nsamples,nvaibles)
 #  Simulation data of nonlinear classification with 200 samples and 1 varible input for 2 classes.
 nclass=2
 ClassificationData=SimData("Nonlinearclassification",nsamples,nvaibles,nclass)

## End(Not run)

snnR documentation built on May 2, 2019, 8:54 a.m.