predict.ocf {ocf} | R Documentation |
Prediction Method for ocf Objects
Description
Prediction method for class ocf
.
Usage
## S3 method for class 'ocf'
predict(object, data = NULL, type = "response", ...)
Arguments
object |
An |
data |
Data set of class |
type |
Type of prediction. Either |
... |
Further arguments passed to or from other methods. |
Details
If type == "response"
, the routine returns the predicted conditional class probabilities and the predicted class
labels. If forests are honest, the predicted probabilities are honest.
If type == "terminalNodes"
, the IDs of the terminal node in each tree for each observation in data
are returned.
Value
Desired predictions.
Author(s)
Riccardo Di Francesco
References
Di Francesco, R. (2023). Ordered Correlation Forest. arXiv preprint arXiv:2309.08755.
See Also
Examples
## Generate synthetic data.
set.seed(1986)
data <- generate_ordered_data(100)
sample <- data$sample
Y <- sample$Y
X <- sample[, -1]
## Training-test split.
train_idx <- sample(seq_len(length(Y)), floor(length(Y) * 0.5))
Y_tr <- Y[train_idx]
X_tr <- X[train_idx, ]
Y_test <- Y[-train_idx]
X_test <- X[-train_idx, ]
## Fit ocf on training sample.
forests <- ocf(Y_tr, X_tr)
## Predict on test sample.
predictions <- predict(forests, X_test)
head(predictions$probabilities)
predictions$classification
## Get terminal nodes.
predictions <- predict(forests, X_test, type = "terminalNodes")
predictions$forest.1[1:10, 1:20] # Rows are observations, columns are forests.
[Package ocf version 1.0.1 Index]