rFerns (version 4.0.0)

predict.rFerns: Prediction with random ferns model

Description

This function predicts classes of new objects with given rFerns object.

Usage

# S3 method for rFerns
predict(object, x, scores = FALSE, ...)

Arguments

object

Object of a class rFerns; a model that will be used for prediction.

x

Data frame containing attributes; must have corresponding names to training set (although order is not important) and do not introduce new factor levels. If this argument is not given, OOB predictions on the training set will be returned.

scores

If TRUE, the result will contain score matrix instead of simple predictions.

...

Additional parameters.

Value

Predictions. If scores is TRUE, a factor vector (for many-class classification) or a logical data.frame (for multi-class classification) with predictions, else a data.frame with class' scores.

Examples

# NOT RUN {
set.seed(77)
#Fetch Iris data
data(iris)
#Split into tRain and tEst set
iris[c(TRUE,FALSE),]->irisR
iris[c(FALSE,TRUE),]->irisE
#Build model
rFerns(Species~.,data=irisR)->model
print(model)

#Test
predict(model,irisE)->p
print(table(
 Predictions=p,
 True=irisE[["Species"]]))
err<-mean(p!=irisE[["Species"]])
print(paste("Test error",err,sep=" "))

#Show first OOB scores
head(predict(model,scores=TRUE))
# }

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