Make Predictions from a "RDTRegressor" Object using labeled dataset and return the R2 score

This function predicts class labels of labeled dataset from a fitted "RDTRegressor" object, and return the corresponding R2 score.

# S3 method for RDTRegressor
score(
  model,
  data,
  key,
  features = NULL,
  label = NULL,
  block.size = NULL,
  thread.ratio = NULL,
  ...
)

Format

S3 methods

Arguments

model

R6Class object
An "RDTRegressor" object for scoring.

key

character
Specifies the ID column in data.

features

character or list of characters, optional
Specifies the feature columns in data.
The specified features must be the same as those in the model training phase.
Defaults to all non-key, non-label columns in data if not provided.

label

character, optional
Specifies the label column in data.
If not provided, defaults to the last non-key column in data.

block.size

integer, optional
The number of rows loaded per time during prediction. 0 indicates load all data at once.
Defaults to 0.

thread.ratio

double, optional
Controls the proportion of available threads that can be used by this function.
The value range is from 0 to 1, where 0 indicates a single thread, and 1 indicates all available threads.
Values between 0 and 1 will use up to that percentage of available threads.Values outside this range are ignored.
Defaults to 0.

Value

numeric
The R2 score of model applied to data.