enet: Elastic net classification panel

In singha53/amritr: Accessory Functions Used by Amrit Singh

Description

build an elastic net classification panel

Usage

enet(X, Y, alpha, lambda = NULL, family, X.test = NULL,
  Y.test = NULL, filter = "p.value", topranked = 50,
  keepVar = NULL)

Arguments

X	nxp matrix - training dataset
Y	categorical variables
alpha	= 1 (lasso), alpha = 0 (ridge), 0 < alpha < 1 (elastic net penalty)
lambda	= strength of elastic net penalty
family	"binomial" or "multinomial"
X.test	nxp matrx - test dataset
filter	= "none" or "p.value"
topranked	= 50 (top number of features to select and build a classifier)

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