rm_reg-class {randomMachines}

S4 class for RM regression

Description

S4 class for RM regression

Details

For more details see Ara, Anderson, et al. "Regression random machines: An ensemble support vector regression model with free kernel choice." Expert Systems with Applications 202 (2022): 117107.

Slots

y_train_hat

a numeric corresponding to the predictions \hat{y}_{i} for the training set

lambda_values

a named list with value of the vector of \boldsymbol{\lambda} sampling probabilities associated with each each kernel function

model_params

a list with all used model specifications

bootstrap_models

a list with all ksvm objects for each bootstrap sample

bootstrap_samples

a list with all bootstrap samples used to train each base model of the ensemble

kernel_weight_norm

a numeric vector corresponding to the normalised weights for each bootstrap model contribution