VT.predict: VT.predict generic function

In prise6/aVirtualTwins: Adaptation of Virtual Twins Method from Jared Foster

Description

VT.predict generic function

Usage

VT.predict(rfor, newdata, type)

## S4 method for signature 'RandomForest,missing,character'
VT.predict(rfor, type = "binary")

## S4 method for signature 'RandomForest,data.frame,character'
VT.predict(rfor, newdata,
  type = "binary")

## S4 method for signature 'randomForest,missing,character'
VT.predict(rfor, type = "binary")

## S4 method for signature 'randomForest,data.frame,character'
VT.predict(rfor, newdata,
  type = "binary")

## S4 method for signature 'train,ANY,character'
VT.predict(rfor, newdata, type = "binary")

## S4 method for signature 'train,missing,character'
VT.predict(rfor, type = "binary")

Arguments

rfor	random forest model. Can be train, randomForest or RandomForest class.
newdata	Newdata to predict by the random forest model. If missing, OOB predictions are returned.
type	Must be binary or continous, depending on the outcome. Only binary is really available.

Value

vector E(Y=1)

Methods (by class)

• rfor = RandomForest,newdata = missing,type = character: rfor(RandomForest) newdata (missing) type (character)

• rfor = RandomForest,newdata = data.frame,type = character: rfor(RandomForest) newdata (data.frame) type (character)

• rfor = randomForest,newdata = missing,type = character: rfor(randomForest) newdata (missing) type (character)

• rfor = randomForest,newdata = data.frame,type = character: rfor(randomForest) newdata (data.frame) type (character)

• rfor = train,newdata = ANY,type = character: rfor(train) newdata (ANY) type (character)

• rfor = train,newdata = missing,type = character: rfor(train) newdata (missing) type (character)

prise6/aVirtualTwins documentation built on May 8, 2019, 6:50 p.m.