Accuracy: accuracy of oblique decision random forest

In ODRF: Oblique Decision Random Forest for Classification and Regression

accuracy of oblique decision random forest

Description

Prediction accuracy of ODRF at different tree sizes.

Usage

Accuracy(obj, data, newdata = NULL)

Arguments

obj	An object of class ODRF, as that created by the function ODRF.
data	Training data of class data.frame in ODRF is used to calculate the OOB error.
newdata	A data frame or matrix containing new data is used to calculate the test error. If it is missing, then it is replaced by data.

Value

OOB error and test error, misclassification rate (MR) for classification or mean square error (MSE) for regression.

See Also

ODRF VarImp plot.Accuracy

Examples

data(breast_cancer)
set.seed(221212)
train <- sample(1:569, 80)
train_data <- data.frame(breast_cancer[train, -1])
test_data <- data.frame(breast_cancer[-train, -1])

forest <- ODRF(diagnosis ~ ., train_data, split = "gini",
parallel = FALSE, ntrees = 50)
(error <- Accuracy(forest, train_data, test_data))

ODRF documentation built on May 31, 2023, 8:22 p.m.