yhat_RF: Fit Random Forest Regression Predictor

In gencve: General Cross Validation Engine

Description

Random Forest prediction on test data

Usage

yhat_RF(dfTrain, dfTest)

Arguments

dfTrain	Data frame for training data. Last column must be the output variable.
dfTest	Data frame for test data. Last column must be the output variable.

Value

The predictions for the test sample

Author(s)

A. I. McLeod

Examples

Xy <- prostate
X <- prostate[,-9]
y <- prostate[,9]
n <- length(y)
d <- 10
set.seed(777513)
iTe <- sample(n, size=d)
iTr <- (1:n)[!match(1:n, iTe, nomatch = 0) > 0]
trdf <- data.frame(X[iTr,], y=y[iTr]) #X, y already defined
tedf <- data.frame(X[iTe,], y=y[iTe])
yhat_plus(trdf, tedf)

Example output

       69        72        10        68        25         6        55        26 
0.9973917 1.7908203 1.0259369 2.7342739 1.4321338 0.2577856 2.9660044 1.8346914 
       73        34 
2.3487090 0.9242967 

gencve documentation built on May 2, 2019, 6:08 a.m.