bestMARSBoost {boostingDEA}

Tuning an MARSBoost model

Description

This funcion computes the root mean squared error (RMSE) for a set of MARSBoost models built with a grid of given hyperparameters.

Usage

bestMARSBoost(
  training,
  test,
  x,
  y,
  num.iterations,
  learning.rate,
  num.terms,
  verbose = TRUE
)

Arguments

training

Training data.frame or matrix containing the variables for model construction.

test

Test data.frame or matrix containing the variables for model assessment.

x

Column input indexes in training.

y

Column output indexes in training.

num.iterations

Maximum number of iterations the algorithm will perform

learning.rate

Learning rate that control overfitting of the algorithm. Value must be in (0,1]

num.terms

Maximum number of reflected pairs created by the forward algorithm of MARS.

verbose

Controls the verbosity.

Value

A data.frame with the sets of hyperparameters and the root mean squared error (RMSE) associated for each model.