bayesian_linear_regression_predict: BayesianLinearRegression Prediction

In mlpack: 'Rcpp' Integration for the 'mlpack' Library

BayesianLinearRegression Prediction

Description

An implementation of the Bayesian linear regression prediction: Given a pre-trained model and a test data set, it provides model predictions.

Usage

bayesian_linear_regression_predict(
  input_model,
  test,
  stddevs = FALSE,
  verbose = getOption("mlpack.verbose", FALSE)
)

Arguments

input_model	Trained BayesianLinearRegression model to use (BayesianLinearRegression).
test	Matrix containing points to regress on (test points) (numeric matrix).
stddevs	Return standard deviations along with predictions. Default value "FALSE" (logical).
verbose	Display informational messages and the full list of parameters and timers at the end of execution. Default value "getOption("mlpack.verbose", FALSE)" (logical).

Value

A list with several components defining the class attributes:

predictions

Matrix of predicted responses, with associated standard deviations if option selected (numeric matrix).

Author(s)

mlpack developers

Examples

# \dontrun{ pred <- predict(model, newdata=X_test) }

mlpack documentation built on July 23, 2026, 1:08 a.m.