ensembleEnet: Build ensemble enet classification panel

In singha53/amritr: Accessory Functions Used by Amrit Singh

Description

Build ensemble enet classification panel

Usage

ensembleEnet(X.trainList, y.train, alphaList, lambdaList,
  family = "binomial", X.testList = NULL, y.test = NULL,
  filter = "none", topranked = 50, keepVarList = NULL)

Arguments

X.trainList	- list of training datasets (nxpi); i number of elements
y.train	- n-vector of class labels (must be a factor)
alphaList	= list of alpha values
lambdaList	= list of lambda values
family	- can be "binomial" or "multinomial"
X.testList	- list of test datasets (nxpi); i number of elements
y.test	- n-vector of class labels (must be a factor)
filter	- pre-filtering of initial datasets - "none" or "p.value"
topranked	- Number of topranked features based on differential expression to use to build classifer
keepVarList	- which variables to keep and not omit (set to NULL if no variables are forced to be kept)

Value

model

testPerf

X.trainList

y.train

alphaList

lambdaList

family

X.testList

y.test

filter

topranked

keepVarList

singha53/amritr documentation built on July 21, 2019, 3:46 p.m.