predictProb: predict probabilities

In EMLasso: Fit (logistic) LASSO when there is missing data in the predictors

Description

predict probabilities

Usage

  predictProb(object, newdata, ..., verbosity = 0)

  ## S3 method for class 'lognetProbabilityReusable'
 predictProb(object,
    newdata, ..., verbosity = 0)

Arguments

object	object that is used to predict the probabilities
newdata	dataset for which the probabilities must be predicted
...	provided for extensibility (S3)
verbosity	The higher this value, the more levels of progress and debug information is displayed (note: in R for Windows, turn off buffered output)

Value

vector of probabilities of the same length as nrow(newdata)

vector of probabilities of the same length as nrow(newdata)

Author(s)

Nick Sabbe [e-mail]

Nick Sabbe [e-mail]

Examples

data(iris)
	iris.nd2<-numdfr(iris)
	y2<-rbinom(nrow(iris), 1, 0.5)
	iris.nic2<-normalImputationConversion(
		scalingParams=typicalScaleAndCenter(),
		transformParams=typicalTransformations())
	iris.cp2<-imputeDs2FitDsProps(iris.nic2,iris.nd2,verbosity=1)

	iris.cvtd2<-imputeDs2FitDs(iris.cp2,ds=iris.nd2,verbosity=3)

	lnet<-glmnet(iris.cvtd2, y2, family="binomial")
	lpw<-lognetProbabilityReusable(lnet, imputeDs2FitDsProperties=iris.cp2, iris.nd2, usecol=5, verbosity=1)
predictProb(lpw, iris.nd2[seq(20),], verbosity=10)

EMLasso documentation built on May 2, 2019, 5:49 p.m.