Make predictions on new data points. — predict.cuda_ml_rand

Make predictions on new data points using a CuML random forest model.

# S3 method for cuda_ml_rand_forest
predict(
  object,
  x,
  output_class_probabilities = NULL,
  cuML_log_level = c("off", "critical", "error", "warn", "info", "debug", "trace"),
  ...
)

Arguments

object	A trained CuML model.
x	A matrix or dataframe containing new data points.
output_class_probabilities	Whether to output class probabilities. NOTE: setting `output_class_probabilities` to `TRUE` is only valid when the model being applied is a classification model and supports class probabilities output. CuML classification models supporting class probabilities include `knn`, `fil`, and `rand_forest`. A warning message will be emitted if `output_class_probabilities` is set to `TRUE` or `FALSE` but the model being applied does not support class probabilities output.
cuML_log_level	Log level within cuML library functions. Must be one of "off", "critical", "error", "warn", "info", "debug", "trace". Default: off.
...	Additional arguments to `predict()`. Currently unused.

Value

Predictions on new data points.