rm_reg-class | R Documentation |
S4 class for RM regression
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.
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
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