predict.tsp.randomForest: prediction function for tsp.randomForest

In BigTSP: Top Scoring Pair based methods for classification

Description

prediction function for tsp.randomForest

Usage

## S3 method for class 'tsp.randomForest'
predict(object, newdata, type = "response", norm.votes = TRUE, predict.all = FALSE, proximity = FALSE, nodes = FALSE, cutoff, ...)

Arguments

object	a tsp.randomForest object
newdata	new data matrix
type	one of response, prob. or votes, indicating the type of output: predicted values, matrix of class probabilities, or matrix of vote counts. class is allowed, but automatically converted to ”response", for backward compatibility.
norm.votes	Should the vote counts be normalized (i.e., expressed as fractions)?
predict.all	Should the predictions of all trees be kept?
proximity	Should proximity measures be computed?
nodes	Should the terminal node indicators (an n by ntree matrix) be return? If so, it is in the ”nodes" attribute of the returned object.
cutoff	A vector of length equal to number of classes. The 'winning' class for an observation is the one with the maximum ratio of proportion of votes to cutoff.
...	not used.

Author(s)

Xiaolin Yang, Han Liu

References

randomForest package.

Examples

library(randomForest)
x=matrix(rnorm(100*20),100,20)
y=rbinom(100,1,0.5)
y=as.factor(y)
fit=tsp.randomForest(x,y)
predict(fit,x[1:10,])

BigTSP documentation built on May 2, 2019, 6:09 a.m.