Function that loads a previously trained vaeac model and continue the training, either on new data or on the same dataset as it was trained on before. If we are given a new dataset, then we assume that new dataset has the same distribution and one_hot_max_sizes as the original dataset.
vaeac_train_model_continue(
explanation,
epochs_new,
lr_new = NULL,
x_train = NULL,
save_data = FALSE,
verbose = 0,
seed = 1
)A explain() object and vaeac must be the used approach.
Positive integer. The number of extra epochs to conduct.
Positive numeric. If we are to overwrite the old learning rate in the adam optimizer.
A data.table containing the training data. Categorical data must have class names \(1,2,\dots,K\).
Logical (default is FALSE). If TRUE, then the data is stored together with
the model. Useful if one are to continue to train the model later using vaeac_train_model_continue().
Boolean. An integer specifying the level of verbosity. Use 0 (default) for no verbosity,
1 for low verbose, and 2 for high verbose.
Positive integer (default is 1). Seed for reproducibility. Specifies the seed before any randomness
based code is being run.
A list containing the training/validation errors and paths to where the vaeac models are saved on the disk.