Description Usage Arguments Value Author(s) References See Also Examples
View source: R/Predict.OTReg.R
This function provides prediction for test data on the trained OTReg
object for the continuous response variable.
1 | Predict.OTReg(Opt.Trees, XTesting, YTesting)
|
Opt.Trees |
An object of class |
XTesting |
An |
YTesting |
Optional. A vector of length |
A list with values
Unexp.Variations |
Unexplained variations based on estimated response and given response. |
Pr.Values |
A vector of length |
Zardad Khan <zkhan@essex.ac.uk>
Khan, Z., Gul, A., Perperoglou, A., Miftahuddin, M., Mahmoud, O., Adler, W., & Lausen, B. (2019). Ensemble of optimal trees, random forest and random projection ensemble classification. Advances in Data Analysis and Classification, 1-20.
Liaw, A. and Wiener, M. (2002) “Classification and regression by random forest” R news. 2(3). 18–22.
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 | # Load the data
data(Galaxy)
data <- Galaxy
#Divide the data into training and test parts
set.seed(9123)
n <- nrow(data)
training <- sample(1:n,round(2*n/3))
testing <- (1:n)[-training]
X <- data[,1:4]
Y <- data[,5]
#Train oTReg on the training data
Opt.Trees <- OTReg(XTraining=X[training,],YTraining = Y[training],t.initial=200)
#Predict on test data
Prediction <- Predict.OTReg(Opt.Trees, X[testing,],YTesting=Y[testing])
#Objects returned
names(Prediction)
Prediction$Unexp.Variations
Prediction$Pr.Values
Prediction$Trees.Used
|
Add the following code to your website.
For more information on customizing the embed code, read Embedding Snippets.