predict.cuda_ml_rand_forest: Make predictions on new data points.

In cuda.ml: R Interface for the RAPIDS cuML Suite of Libraries

Description

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

Usage

## S3 method for class '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.

cuda.ml documentation built on Jan. 8, 2022, 9:06 a.m.