Predict Using GatingTreeRandomForest Model

This function uses the GatingTreeRandomForest model stored in a `FlowObject` to make predictions on a new dataset. It prepares the test dataset, applies the gating conditions specified in the model, and then uses the Random Forest model to predict outcomes.

Usage

predictGatingTreeRandomForest(train_x, test_y)

Arguments

train_x

A `FlowObject` that contains a previously fitted `GatingTreeRandomForest` model.

test_y

A `FlowObject` containing the test dataset for prediction.

Value

A list containing:

• predicted_scores: The probabilities predicted by Random Forest.

• test_data: The test data used for Random Forest.

• results_pred: A data frame for predicted scores.

See also

Other GatingTree Random Forest Analysis: GatingTreeRandomForest()

Examples

if (FALSE) { # \dontrun{
  train_x <- GatingTreeRandomForest(train_x)
  predictions <- predictGatingTreeRandomForest(train_x, test_y)
  head(predictions$predicted_scores)
} # }